A DVS-based optical cable early warning control method and early warning system

Abstract

The present invention relates to the field of optical cable early warning, and in particular to an optical cable early warning control method and early warning system based on DVS. When receiving brightness change data sent by a DVS sensor, the brightness change data is parsed, the path of the brightness change data is identified, and the target position of the brightness change data is determined; the environmental data of the target position is obtained, and the brightness change data is verified according to the environmental data; based on the verification result, when the target position meets the abnormal condition, the abnormal parameters of the target position are analyzed; according to the abnormal parameters of the target position, the abnormal change parameters of the target position are predicted; the control strategy is determined according to the abnormal parameters and the predicted abnormal change parameters, and based on the control strategy, the abnormal data of the target position generates early warning information and sends it to the management end. By considering environmental factors, the abnormality of the optical cable can be accurately detected, and possible faults can be predicted, providing efficient control and achieving accurate monitoring of the optical cable.

Description

Technical Field

[0001] The present application relates to the field of optical cable early warning technology, and in particular to an optical cable early warning management and control method and an early warning system based on DVS. Background Art

[0002] Optical fiber communication has become an important infrastructure in modern communication networks. The construction and maintenance scale of optical fiber networks continues to expand, but in the operation of optical cables, damage, degradation or failure of optical cables often occur, affecting the stability and security of communications.

[0003] In the existing optical cable warning technology, DVS (Distributed Vibration Sensor) sensors or similar optical fiber sensors are generally used to detect abnormal conditions of optical cables. These sensors use the optical properties of optical fibers (such as light attenuation, reflection, etc.) to sense and determine whether the optical cable is faulty or damaged. However, since DVS sensors are very sensitive to light detection. This means that even if there is no fault in the optical cable itself, external environmental changes (such as temperature changes, construction vibrations, strong winds, etc.) can affect the transmission of optical signals, causing the system to misjudge that the optical cable is damaged. For example, weather changes or external interference can cause signal fluctuations, and it is difficult to distinguish whether these fluctuations are caused by environmental factors or due to the failure of the optical cable itself. Secondly, although the existing technology can detect signal abnormalities, it is difficult to accurately determine the type of optical cable fault (such as damage, bending, contamination, or poor contact). The existing system can only give a vague abnormal warning and lacks more detailed fault information. After receiving the alarm, maintenance personnel often need to conduct on-site inspections to confirm the specific fault type and cause. Since the abnormal conditions of the optical cable cannot be accurately identified, maintenance personnel face greater uncertainty when making decisions. This can lead to delayed repair strategies or even inappropriate repair solutions.

[0004] Therefore, the prior art has defects and needs to be improved. Summary of the invention

[0005] In order to solve one or several problems in the prior art, the main purpose of the present application is to provide a DVS-based optical cable early warning management method and early warning system.

[0006] In order to achieve the above-mentioned invention object, the present application proposes a DVS-based optical cable early warning control method, the method comprising:

[0007] When receiving the brightness change data sent by the DVS sensor;

[0008] parsing the brightness change data, performing path identification on the brightness change data, and determining a target position of the brightness change data;

[0009] Acquire environmental data of the target location, and verify the brightness change data according to the environmental data;

[0010] Based on the verification result, when the target position meets the abnormal condition, analyzing the abnormal parameters of the target position;

[0011] According to the abnormal parameters of the target position, predicting the abnormal change parameters of the target position;

[0012] A control strategy is determined according to the abnormal parameters and the predicted abnormal change parameters, and based on the control strategy, an abnormal data of the target location generates warning information and sends it to a management terminal.

[0013] The embodiment of the present application also provides an optical cable early warning system based on DVS, including:

[0014] The receiving module is used for receiving the brightness change data sent by the DVS sensor;

[0015] an identification module, used to analyze the brightness change data, perform path identification on the brightness change data, and determine a target position of the brightness change data;

[0016] An acquisition module, used for acquiring environmental data of the target location, and verifying the brightness change data according to the environmental data;

[0017] A verification module, configured to analyze abnormal parameters of the target location when the target location meets an abnormal condition based on a verification result;

[0018] A prediction module, used for predicting abnormal change parameters of the target location according to the abnormal parameters of the target location;

[0019] The sending module is used to determine a control strategy according to the abnormal parameters and the predicted abnormal change parameters, and based on the control strategy, generate warning information of the abnormal data of the target location and send it to the management end.

[0020] The present application also provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of any one of the above methods when executing the computer program.

[0021] The present application also provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of any of the above-mentioned methods are implemented.

[0022] The optical cable early warning control method and early warning system based on DVS in the embodiment of the present application can accurately locate the location where the optical cable abnormality occurs through the brightness change data collected by the DVS sensor and the path recognition technology. This process ensures the rapid identification and accurate positioning of the fault. The system can effectively distinguish the brightness change caused by the external environment change from the fault of the optical cable itself through the real-time acquisition and verification of the environmental data, thereby avoiding false alarms and misjudgments and improving the accuracy of fault identification. By analyzing the abnormal parameters behind the brightness change, combined with the prediction model of machine learning and historical data, the system can predict the possible future fault trend of the optical cable in advance. This prediction capability can help to discover potential problems in time, reduce the occurrence of sudden failures, and improve the overall reliability of the system. Through the comprehensive analysis and prediction of abnormal parameters, the system can formulate targeted control strategies, such as strengthening monitoring, local repair and other measures, and generate real-time warning information to send to the management end. This intelligent early warning and response mechanism ensures that the management personnel can respond in the first time and implement fast and effective maintenance or protection measures, thereby greatly improving the efficiency of optical cable maintenance and emergency response capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 This is a flow chart of a DVS-based optical cable early warning control method according to an embodiment of the present application;

[0024] Figure 2 This is a flow chart of a DVS-based optical cable early warning control method according to an embodiment of the present application;

[0025] Figure 3 This is a schematic block diagram of the structure of an optical cable early warning system based on DVS according to an embodiment of the present application;

[0026] Figure 4 A schematic block diagram of the structure of a computer device according to an embodiment of the present application.

[0027] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0029] Reference Figure 1 In an embodiment of the present application, a DVS-based optical cable early warning management method is provided, the method comprising:

[0030] S1, when receiving the brightness change data sent by the DVS sensor;

[0031] S2, analyzing the brightness change data, performing path identification on the brightness change data, and determining a target position of the brightness change data;

[0032] S3, acquiring environmental data of the target location, and verifying the brightness change data according to the environmental data;

[0033] S4. Based on the verification result, when the target position meets the abnormal condition, analyzing the abnormal parameters of the target position;

[0034] S5. predicting abnormal change parameters of the target location according to the abnormal parameters of the target location;

[0035] S6. Determine a control strategy according to the abnormal parameters and the predicted abnormal change parameters, and based on the control strategy, generate warning information of the abnormal data of the target location and send it to the management end.

[0036] As described in the above steps S1-S3, the DVS sensor is a sensor based on optical fiber technology. It senses changes in the external environment by monitoring phenomena such as vibration, temperature change or light attenuation in the optical fiber. The sensor detects the brightness change of the optical fiber in real time and sends these change data to the early warning system. Brightness changes are usually caused by interference from the external environment of the optical fiber (such as vibration, physical stretching, etc.) or damage to the optical cable itself (such as breakage or poor contact). By analyzing these data, the health status of the optical cable can be monitored. By collecting and transmitting brightness change data in real time, it is possible to capture small changes in the optical cable in time, and then determine whether the optical cable is disturbed by the external environment or fails. By accurately monitoring brightness changes, continuous monitoring of the optical cable can be achieved to ensure that abnormalities can be discovered and measures can be taken as soon as possible. After the system receives the brightness change data, it first performs data analysis. The analysis process includes extracting relevant brightness change information from the transmission path of the optical fiber, and determining the specific location of these change data in the optical fiber through a path recognition algorithm. Since optical fiber sensors are usually installed at different positions of the optical cable, the system needs to identify which positions have the most significant brightness change data and further locate the specific target position. Optical cables are generally long and may have multiple monitoring points, so it is necessary to match the brightness change data with the specific physical location. Path identification can effectively determine the exact location of the fault or anomaly, thereby helping maintenance personnel to locate the problem area in a timely manner and improve the accuracy of optical cable monitoring. Accurately locating the source of brightness change can quickly lock the abnormal area, avoid false alarms or omissions, and help shorten the fault location time. After determining the target location, the system further obtains environmental data (such as temperature, humidity, wind speed, etc.) of the location. These environmental data are usually provided by other sensors (such as meteorological sensors). The role of environmental data is to verify the brightness change data and determine whether the brightness change is caused by environmental factors (such as weather changes, wind force, temperature fluctuations, etc.) or by damage or failure of the optical cable itself. Environmental factors are one of the reasons for the change in optical fiber brightness. For example, temperature changes, environmental obstruction, or drastic changes in wind speed may affect the performance of the optical cable. Therefore, relying solely on brightness change data for judgment may misjudge the fault. Introducing environmental data verification can effectively distinguish between errors caused by changes in the external environment and anomalies caused by failures of the optical cable itself. The introduction of environmental data improves the accuracy of the optical cable monitoring system, avoids false alarms or misjudgments due to external environmental factors, and thus enhances the reliability of the system.

[0037] As described in the above steps S4-S6, after verifying the brightness change data, if the change at the location is confirmed to meet the abnormal conditions (such as environmental factors are not sufficient to explain these changes), the system will further analyze the abnormal parameters at the location. Abnormal parameters may include the vibration amplitude of the optical fiber, the degree of light attenuation, the bending or damage of the optical fiber, etc. These parameters can reflect whether the optical cable is damaged or whether there is a hidden danger of failure. Abnormal parameters are important indicators for determining whether the optical cable has failed. By analyzing these parameters, the system can have a more comprehensive understanding of the health status of the optical cable, rather than relying solely on a single brightness change data. This can improve the accuracy and reliability of fault diagnosis. The system can accurately determine the specific abnormal conditions of the optical cable, provide a basis for subsequent fault prediction and maintenance decisions, reduce the possibility of false alarms, and improve the diagnostic accuracy of optical cable faults. After obtaining the abnormal parameters, the system analyzes the change trends of these parameters through a prediction model and predicts the abnormal changes that may occur in the future at the location. For example, if the vibration or light attenuation of the optical fiber in a certain area continues to increase, the system can predict that the location may be further damaged or even a more serious fault may occur. The prediction process usually relies on historical data and machine learning algorithms to infer future change trends through data mining technology. Prediction can identify potential problems in advance, so that the optical cable is not discovered until a major failure occurs. Prediction not only allows managers to take preventive measures in advance, but also helps to reasonably plan maintenance and resource scheduling. Predicting abnormal changes in advance can effectively reduce the probability of sudden failures and provide maintenance personnel with more time to repair, thereby ensuring the stable operation of the optical cable. After analyzing the abnormal parameters and predicted abnormal changes, the system formulates corresponding control strategies based on this information. These strategies may include strengthening the monitoring of the target location, protecting the surrounding area, and repairing the optical cable. After the control strategy is determined, the system will generate an early warning for the abnormal information of the target location and send it to the management end. The management end can respond quickly and take corresponding measures based on these early warning information. Real-time early warning can ensure that managers can respond quickly when abnormalities occur in the optical cable. By formulating control strategies based on abnormal predictions, optical cable maintenance can be carried out accurately and effectively, preventing further expansion of faults and ensuring the safety of the optical cable network. The generated early warning information helps managers make decisions at the first time, improves the maintenance efficiency and emergency response speed of the optical cable, reduces maintenance costs, and ensures the continuous and stable operation of the optical cable system.

[0038] As mentioned above, by combining the brightness change data collected by the DVS sensor with the path recognition technology, the system can accurately locate the location where the optical cable abnormality occurs. This process ensures the rapid identification and accurate location of the fault. By acquiring and verifying the environmental data in real time, the system can effectively distinguish the brightness change caused by the external environment change from the fault of the optical cable itself, thereby avoiding false alarms and misjudgments and improving the accuracy of fault identification. By analyzing the abnormal parameters behind the brightness change, combined with the prediction model of machine learning and historical data, the system can predict the possible future fault trends of the optical cable in advance. This prediction capability can help to discover potential problems in time, reduce the occurrence of sudden failures, and improve the overall reliability of the system. Through comprehensive analysis and prediction of abnormal parameters, the system can formulate targeted management and control strategies, such as strengthening monitoring, local repair and other measures, and generate real-time warning information to send to the management end. This intelligent early warning and response mechanism ensures that managers can respond in the first time and implement fast and effective maintenance or protection measures, thereby greatly improving the efficiency of optical cable maintenance and emergency response capabilities.

[0039] Reference Figure 2 In one embodiment, the method of verifying the brightness change data according to the environmental data includes:

[0040] S31, acquiring environmental data of the target location, combining the environmental data with the brightness change data, and verifying whether the environmental data and the brightness change data match;

[0041] S32, when the brightness change data matches the environmental data, obtaining the change trend of the brightness change data and the environmental data within a preset time period;

[0042] S33, if the change trends of the brightness change data and the environmental data within the preset time period match, it is determined that the optical cable does not meet the warning condition;

[0043] S34: When the brightness change data does not match the environmental data, it is determined that the optical cable meets the warning condition.

[0044] As described in the above steps, it is necessary to collect environmental data of the target location (i.e., the location where the optical cable is located), including but not limited to temperature, humidity, vibration, environmental objects, etc. These data are monitored in real time by sensors and fed back to the system. Environmental data is a comprehensive reflection of the environmental conditions around the optical cable, which can help identify the impact of environmental changes (such as weather changes) on the optical cable signal. Environmental changes may directly or indirectly affect the transmission signal of the optical cable. For example, temperature changes may affect the expansion and contraction of the optical fiber, thereby affecting the signal brightness. Obtaining environmental data helps to take environmental factors into consideration and reduce false alarms caused by external environmental changes. Ensure that the system can obtain real-time environmental status to provide background information for subsequent brightness change data analysis. Effectively eliminate erroneous judgments caused by environmental interference to ensure that subsequent data analysis is more accurate. After obtaining environmental data, the system compares and analyzes these data with brightness change data. Through data matching, the system determines whether the brightness change conforms to the law of environmental changes. The matching analysis of environmental data and brightness change data can help distinguish normal brightness fluctuations caused by environmental changes from possible optical cable faults. For example, if the temperature suddenly rises and the brightness does not change accordingly, it may be that the environmental change has not affected the optical cable, and the brightness change may be caused by a fault. Through this matching verification, the system can quickly identify which brightness changes are caused by environmental factors and which may indicate problems with the optical cable. Improve the accuracy of fault identification and reduce false alarms caused by changes in the external environment. If the brightness change data matches the environmental data, the system will further analyze the brightness change trend and environmental data trend within a preset time period. Trend analysis helps capture long-term change patterns, not just instantaneous fluctuations. Short-term brightness changes may only be instantaneous interference, and by observing trend changes over a longer period of time, the system can better identify potential fault signals. For example, when the temperature rises over a long period of time, the brightness of the optical cable should also gradually decrease. If the change trends of the two are inconsistent, it may indicate a fault in the optical cable. Trend analysis can significantly improve the accuracy of system judgment. By comparing the change trends of the environment and brightness, false alarms caused by short-term sudden environmental changes can be effectively excluded, and whether there are long-term and continuous abnormal conditions, thereby ensuring sensitivity and response speed to faults. If the brightness change data matches the trend of the environmental data, the system will determine that the optical cable does not meet the warning conditions, that is, no potential fault risk is detected. At this time, the amplitude of the brightness change is consistent with the trend of environmental changes, indicating that the optical cable is in normal condition. By setting the warning conditions, the system can filter out the brightness fluctuations caused by environmental changes and focus on the real optical cable faults. The warning will only be triggered when the brightness change trend does not match the environmental data significantly. This judgment can reduce the system's false alarms and improve the stability of the optical cable monitoring system. When the system detects normal environmental and brightness changes, it will not issue false alarms, reducing interference to operation and maintenance personnel.When the brightness change data does not match the environmental data, the system will determine that the optical cable meets the early warning conditions. At this time, the change in brightness does not match the environmental changes as expected, which may indicate that there is a problem with the optical cable (such as failure, damage, looseness, etc.). The mismatch between brightness and environmental data usually means that the possibility of failure of the optical cable increases. For example, changes in environmental conditions cause temperature changes, but the brightness does not change accordingly, which may indicate that the optical cable does not respond normally to environmental changes and there is a potential failure.

[0045] In another embodiment, among the occlusion factors of environmental data, especially in the optical cable monitoring system, the impact of occlusion on the signal can be misleading like environmental changes. Occlusion means that the optical cable monitoring area may be blocked by objects or environmental changes, causing interference or abnormality in the signal obtained by the sensor. Occlusion phenomena usually include trees, buildings, vehicles or other moving objects, etc., whose presence may change the optical signal on the surface of the optical fiber or cause the sensor to receive erroneous light brightness data. The presence of obstructions can be detected and confirmed by deploying additional sensors (such as infrared sensors, image recognition sensors, etc.). These sensors can monitor objects near the optical cable and provide occlusion data, which is input into the analysis model together with environmental data (such as temperature, humidity, etc.). The combination of occlusion information and brightness change data can help determine whether the brightness change is caused by object occlusion or a fault in the optical cable itself. For example, if the brightness change corresponds to the occlusion data, it is likely that the signal is weakened due to object occlusion, rather than a fault in the optical cable.

[0046] In one embodiment, the combining the environmental data and the brightness change data to verify whether the environmental data and the brightness change data match, the method includes:

[0047] Acquiring the environmental data and brightness change data, wherein the environmental data includes weather parameters and environmental object parameters;

[0048] Based on the time series, extract the change characteristics of the brightness change data, including the brightness change frequency and duration; extract the change characteristics of the environment data, including the environment change rate and duration;

[0049] Calculate the correlation coefficient between the environmental data and the brightness change data;

[0050] When the correlation coefficient is less than a preset coefficient threshold, it is determined that the generation of the brightness change data does not match the environmental data.

[0051] As mentioned above, environmental data includes weather parameters (such as temperature, humidity, wind speed, precipitation, air pressure, etc.) and environmental parameters (such as the presence of surrounding obstacles, light intensity, noise, etc.). These data provide background information about changes in the external environment. Brightness change data is the signal strength change data collected by the optical cable monitoring system, which reflects the attenuation or change of the optical signal received by the optical cable. Brightness change frequency refers to the frequency of occurrence of brightness changes in a time series. Frequent brightness changes may indicate some rapidly changing environmental factors or interference. Brightness change duration refers to the length of time from the beginning to the end of the brightness change. Long-term changes may indicate a persistent abnormality of the system or the long-term impact of environmental factors. Brightness change frequency and duration are important features for detecting anomalies. If brightness changes occur more frequently or last longer, it may indicate that the abnormality of the optical signal is caused by persistent external factors (such as obstructions, equipment failures, etc.) rather than short-term environmental changes (such as instantaneous changes in wind speed). These features help the system understand the nature of brightness changes, identify whether it is an instantaneous short-term change or a persistent long-term interference, and provide clues for subsequent matching analysis. The environmental change rate refers to the speed at which environmental data (such as temperature, humidity, wind speed, etc.) changes within a certain period of time. Rapid or drastic changes in the environment may usually affect the signal transmission of the optical cable (such as sudden rainfall or increased wind speed). It refers to the length of time that environmental factors change and remain within a range of changes. For example, it may take a certain amount of time for temperature changes to affect the stability of the optical signal. The environmental change characteristics help determine whether the external environment has changed sufficiently, which may in turn affect the brightness change. By monitoring the change characteristics of environmental data, the system can determine whether there are environmental factors related to the change of the optical signal. It helps to understand the dynamic changes of the environment, determine whether the optical signal is affected by specific environmental conditions (such as rapid temperature changes, heavy rain, etc.), and improve the accuracy of anomaly detection. Calculate the correlation coefficient between the brightness change characteristics (such as frequency, duration) and the environmental data change characteristics (such as change rate, duration). The correlation coefficient reflects the similarity of the changes between the two. If the correlation coefficient is high, it means that the environmental change is strongly correlated with the brightness change, and it may be that the environmental factor directly affects the optical signal. The correlation coefficient is an important indicator to measure whether the environmental change and the brightness change match. If the change patterns of the two are highly consistent, it may indicate that the brightness change is indeed related to the environmental change; conversely, a low correlation coefficient may be caused by other factors (such as equipment failure, obstructions, etc.). By calculating the correlation coefficient, the system can objectively quantify the matching degree between the brightness change and the environmental data, and help determine whether the brightness change is caused by environmental changes. If the calculated correlation coefficient is less than the preset threshold (usually set based on historical data and experience), the system will consider that the brightness change does not match the environmental change data, which may be caused by other factors (such as obstructions, equipment failure, etc.). At this time, the system can trigger an alarm to notify the operation and maintenance personnel to conduct further inspection.The purpose of setting a threshold is to avoid misjudging a fault due to normal environmental fluctuations (such as slight effects of weather changes). By setting a reasonable threshold, the system can ensure that an alarm is only issued when environmental changes do not match brightness changes, avoiding excessive alarms.

[0052] In one embodiment, the method of analyzing the abnormal parameters of the target location includes:

[0053] According to the target position of the brightness change data, using infrared imaging to obtain temperature data of the target position;

[0054] Perform layer overlap processing on the temperature data and the brightness change data to obtain images with the same spatial resolution as the temperature data and the brightness change data;

[0055] Based on the result of the layer repainting process, the spatial resolution image is geometrically aligned and the heat accumulation area of ​​the temperature fluctuation is marked;

[0056] Inputting the heat accumulation area into a preset pattern matching model, analyzing the optical cable damage type in the heat accumulation area through the pattern matching model, and outputting the analysis result, wherein the optical cable damage type includes cracks, local fractures or compression deformation;

[0057] The abnormal parameters of the target position are determined according to the optical cable damage type.

[0058] As mentioned above, brightness change data refers to information obtained through monitoring or sensors that reflects the brightness change of the target position, which is usually used to indicate the activity or state change of the target area. The temperature distribution of the target position is obtained by an infrared camera. Infrared imaging technology can detect the change in the surface temperature of the object and generate a temperature image. When the optical cable is damaged, it usually shows local temperature anomalies, and infrared imaging can capture these anomalies. Brightness changes are often related to temperature changes, especially under the influence of mechanical damage or changes in the external environment, temperature fluctuations will cause brightness changes. Therefore, guiding the acquisition of temperature data through brightness change data helps to locate and capture the temperature anomaly areas related to optical cable damage in a targeted manner. This process ensures that potential damage areas can be efficiently located and captured, and the damage characteristics are further confirmed through temperature data. Infrared imaging provides an intuitive and accurate thermal distribution map, which helps to identify damage problems that are not easy to detect (especially when the inside of the optical cable is damaged, it may not be able to detect small cracks or deformations on the surface of the optical cable, especially deep cracks or cracks located at the joints, because these damages may not produce significant light intensity changes in the early stage, so red heat detection can overcome this defect). The temperature data image and the brightness change data image are superimposed in the same coordinate system to ensure that the spatial resolution of the two is consistent. This means that the two data will form a unified image layer, and the image overlap allows them to be compared and analyzed with each other. The key to layer overlap processing is to ensure that the temperature image and the brightness image are perfectly aligned in space, so as to avoid data deviation caused by different resolutions. Since the brightness change and temperature data come from different measurement methods, if their resolutions and spatial positioning are inconsistent, it may lead to inaccurate data docking, affecting the accuracy of subsequent analysis. Through layer overlap processing, it is possible to ensure that the two data are aligned in space, which is convenient for further analysis and comparison. Through layer overlap, temperature anomalies and brightness changes can be reflected in the same image, so as to more intuitively present the area of ​​optical cable damage. The overlapped image provides a unified reference framework, which is helpful for subsequent geometric position correspondence and damage identification. Geometric position correspondence refers to the precise correspondence of temperature data and brightness change data after layer overlap in spatial coordinates to ensure that they can reflect temperature fluctuations and brightness changes in the same area. Based on the distribution of temperature fluctuations, identify and mark the heat accumulation area. Usually, these areas are where the optical cable is damaged or there are potential problems. For example, local damage to the optical cable will cause the temperature in the area to rise, forming heat accumulation. Accurate geometric position correspondence ensures accurate spatial docking of temperature data and brightness change data. The marking of heat accumulation areas is a response to abnormal temperature fluctuations, which can focus on the core area of ​​the damaged optical cable and provide a clear target for subsequent analysis. After marking the heat accumulation area, the system can focus on analyzing these hot spots where damage may exist.By focusing on these areas, the efficiency and accuracy of damage analysis can be effectively improved, and interference from too many irrelevant areas can be avoided. Based on machine learning or image recognition algorithms, a pattern matching model trained with historical data is used to analyze the heat accumulation area. The model can identify and classify the types of optical cable damage corresponding to the heat accumulation area, such as cracks, local fractures, or compression deformation. The temperature fluctuation characteristics of the heat accumulation area will vary according to different types of damage, and the pattern matching model can classify and judge based on the learned damage characteristics. Different types of optical cable damage usually show different temperature fluctuation patterns. By presetting the pattern matching model, the existing damage data can be used to intelligently classify the newly appeared heat accumulation area, so as to accurately determine the damage type. This step can realize automatic damage type identification, reduce manual intervention, and improve the accuracy of damage analysis. The model can quickly identify different types of optical cable damage and provide more detailed diagnostic reports, which is helpful for subsequent maintenance and processing. According to the damage type (such as cracks, local fractures, or compression deformation), the system will output corresponding abnormal parameters, such as temperature fluctuation amplitude, damage extension speed, area size, etc. These abnormal parameters reflect the severity of the damage and the possible scope of impact. Different types of damage have different effects on optical cables. Cracks may cause local temperature fluctuations, while local breaks or compression deformation may cause temperature anomalies in a larger area. By determining abnormal parameters based on the damage type, maintenance personnel can be provided with targeted judgment basis and treatment solutions.

[0059] In one embodiment, the method of predicting the abnormal change parameter of the target position according to the abnormal parameter of the target position includes:

[0060] Obtaining historical data of the optical cable damage type and target location;

[0061] Performing data analysis on the historical data of the optical cable damage type and the target location, and determining whether the optical cable damage type satisfies the damage extension law of the historical data;

[0062] If the optical cable damage type does not satisfy the damage extension law of historical data, obtaining the optical cable structure parameters at the target location;

[0063] The optical cable structural parameters and the optical cable damage type are used to simulate the propagation path, speed and final damage of the damage;

[0064] According to the propagation path, speed and final damage of the simulated damage, the prediction of abnormal change parameters of the target location is completed.

[0065] As mentioned above, the type of optical cable damage refers to the type of damage suffered by the optical cable under different circumstances, such as external force damage (such as mechanical compression, shearing, etc.). The historical data of the target location includes the damage history record of the target location (i.e., the location of the optical cable), environmental data (such as temperature, humidity, air pressure, etc.), and equipment operation status. These historical data provide background information for subsequent analysis, helping to analyze the current damage situation and its possible changes. Historical data is the basis for predictive analysis. By analyzing historical data, we can understand the damage type, frequency and cause of the optical cable at the target location, and reveal the expansion law and evolution trend of the damage. This is an important prerequisite for predicting future abnormal change parameters. By collecting historical data on optical cable damage, we can provide rich data support for subsequent analysis of the damage expansion law, ensuring that the prediction model has sufficient historical basis. By performing statistical analysis on historical data, we can evaluate the occurrence pattern and development trend of optical cable damage types. At this time, the analysis model may apply regression analysis, cluster analysis or machine learning methods to identify the expansion law of damage in historical data. For example, a certain type of damage may expand at a specific speed and path. The expansion of optical cable damage often follows certain laws, such as certain environmental factors or physical factors that cause the expansion of the damage range. Therefore, by judging whether the current damage conforms to the historical expansion law, its subsequent changes can be effectively predicted. Through this step of analysis, the system can judge whether the current damage conforms to the historical expansion trend. If the damage pattern does not conform to the historical law, it indicates that there may be new external factors or unknown problems, which require further in-depth analysis. Optical cable structural parameters: including the physical properties of the optical cable (such as the material type, structure, bending radius, length, stress state, etc. of the optical cable). These parameters describe the actual state and structural characteristics of the optical cable, which are closely related to the damage expansion of the optical cable. When the damage type of the optical cable does not conform to the historical law, it means that there is an abnormality in the expansion mode or speed of the damage. At this time, by obtaining the structural parameters of the optical cable, the potential cause of the damage expansion can be further understood. The structural parameters of the optical cable are crucial for simulating the path and speed of damage expansion. Obtaining the structural parameters of the optical cable helps to identify new patterns of damage expansion and ensure that the prediction model can accurately reflect the actual physical situation of the optical cable. If the damage pattern is abnormal, the acquisition of these structural parameters will provide key clues to help correct the prediction model and avoid incorrect prediction results. Based on the structural parameters and historical data of the optical cable, numerical simulations (such as finite element analysis, mechanical modeling, etc.) are used to infer how damage propagates in the optical cable. These simulations take into account the damage's extension path (for example, along a certain part of the optical cable) and speed (the rate at which the damage propagates). The simulation also predicts the final state of the damage (such as whether it will cause complete failure of the optical cable or local damage). The purpose of simulating the damage propagation path and speed is to accurately predict the possible long-term impact of the damage.If the cable structure changes, the damage expansion mode and speed may be different from the historical law, so detailed simulation must be carried out to obtain more accurate predictions. This step helps to fully understand the dynamic changes of damage. Through simulation analysis, the progress of cable damage under different conditions can be predicted, and potential dangers can be discovered in advance. Through simulation, preventive measures can be taken before the damage is fully manifested, thereby improving the predictability and accuracy of cable maintenance. Based on the simulation results of the previous steps, the system combines the specific environmental factors of the target location, the characteristics of the cable structure and the damage propagation simulation, and finally predicts the abnormal change parameters of the target location. These abnormal change parameters may include the degree of damage to the cable, the speed of damage, and the area that may be affected. By integrating various types of information (historical data, cable structure parameters, damage expansion laws, etc.), it is possible to derive the abnormal changes that may occur in the target location in the future, so as to take preventive and repair measures in advance. Through this prediction step, the system can identify possible faults or abnormal areas in advance to avoid accidental damage or system downtime. The predicted abnormal change parameters provide key information required by operation and maintenance personnel, helping them to intervene in time and avoid serious damage.

[0066] In one embodiment, the method of determining a control strategy according to the abnormal parameters and the predicted abnormal change parameters includes:

[0067] Determining the damage level of the target location according to the abnormal parameters and the predicted abnormal change parameters;

[0068] When the damage level of the target location is primary damage, analyzing the impact area of ​​the target location, determining a traffic scheduling path according to the impact area, the scheduling path is used to control the traffic to bypass the target location, and determining a primary damage control strategy based on the traffic scheduling path;

[0069] When the damage level of the target location is high-level damage, identify whether the spare optical cable is occupied. If the spare optical cable is not occupied, transfer the traffic of the current damaged optical cable to the spare optical cable. If the spare optical cable is occupied, encrypt the traffic of the current damaged optical cable, and determine the management and control strategy of high-level damage based on the spare optical cable or traffic encryption.

[0070] As mentioned above, abnormal parameters and abnormal change parameters are usually derived from data analysis of temperature changes, brightness changes, etc. of optical cable damage, reflecting the severity and change trend of damage. Abnormal change parameters are mainly based on historical data and prediction algorithms to speculate the possible expansion or further deterioration of damage. Based on these abnormal parameters, the severity of damage can be judged using preset standards or algorithm models (such as threshold judgment, machine learning classification model, etc.). Generally, damage levels are divided into primary damage and advanced damage. Primary damage may be slight and local damage, while advanced damage may involve damage in a wider range and even affect the overall operation of the optical cable. The classification of damage levels helps to take different countermeasures for different situations. By distinguishing between primary damage and advanced damage, more refined management and control can be achieved to avoid excessive intervention or improper handling. Based on different levels of damage, subsequent management and control strategies can be adjusted in a targeted manner. Primary damage usually means that the optical cable is slightly damaged, which may not immediately cause the system to fail, but may affect the signal or data transmission in a specific area. By analyzing the scope of the damage's impact on the surrounding environment or equipment, the system can determine which areas are affected and then identify areas that need to be bypassed. According to the location of the affected area, the system will automatically design a traffic scheduling path, that is, determine which data flows need to bypass the damaged area to avoid continuing to transmit through the damaged area, ensuring the stability of the entire network. The traffic scheduling path can be calculated by an optimization algorithm to ensure the minimum impact. Primary damage usually does not require immediate switching of spare optical cables or high-intensity treatment measures. By adjusting the traffic scheduling path, the impact of damage on the network can be effectively reduced. Traffic detour can not only ensure normal transmission, but also relieve and treat the damaged area. The effect of this step is to ensure that network traffic is not seriously affected in the case of primary damage, and can quickly return to normal state, avoiding a wider range of network interruptions due to the expansion of damage. For example, the control strategy may include dynamically adjusting the data transmission priority, reducing the traffic demand for the damaged area, or restricting the use of certain services to ensure the reasonable allocation of resources. In the case of primary damage, controlling the flow of traffic is the most critical. By adjusting the traffic scheduling, further damage to the optical cable can be effectively avoided, and interference with other areas or systems can be reduced. In addition, the control strategy can ensure the stable operation of the network and avoid the waste of resources caused by excessive maintenance. The control strategy effectively disperses the impact of the damaged area of ​​the optical cable, and can perform necessary repair work without causing too much interference to the system, ensuring uninterrupted business and extending the life cycle of the system. Advanced damage usually refers to large-scale or severe damage, which may cause the breakage of the optical cable, severe temperature fluctuations, etc. In this case, the system needs to quickly identify whether the damage affects the core function of the optical cable. The system first checks whether there is a spare optical cable available.If the backup cable has not been occupied, the traffic can be directly transferred; if the backup cable has been occupied, other alternatives need to be considered, such as encrypting the traffic. Advanced impairments involve the core functions of the system and often require a quick response. Backup cables can provide an efficient alternative path to ensure that the impact of cable damage on the entire system is minimized. By checking the status of the backup cable in advance, you can ensure that decisions are made quickly and accurately. The system can transfer traffic in time when advanced impairments occur to avoid system paralysis. The effective use of backup cables or traffic encryption can ensure that the network continues to operate and ensure service continuity and reliability. When the backup cable is not occupied, the system will automatically transfer the traffic of the damaged cable to the backup cable. This can be done through traffic redirection, network topology adjustment, etc., to ensure that data continues to be transmitted without being affected by the damaged cable. When the backup cable is occupied and cannot provide more bandwidth, the system will take encryption measures. Encrypting traffic means increasing data traffic within the existing bandwidth by increasing the density of data transmission or optimizing the transmission protocol to ensure that data on the damaged cable is not lost. Advanced impairments often mean that some or all of the functions of the optical cable are not functioning properly, so traffic diversion or encryption are effective countermeasures. Traffic diversion ensures that services are not affected by using spare optical cables, while encryption is an efficient emergency response method that can meet network needs as much as possible when bandwidth resources are limited. With these two methods, the system can flexibly respond to advanced impairments and ensure service continuity. Even if the spare optical cable is occupied, traffic encryption ensures that traffic on the damaged optical cable is not lost, thereby maintaining stable network operation and normal business operations. Based on the decision of spare optical cable or traffic encryption, the system will output corresponding management and control policies, which may include adjusting traffic distribution, priority setting, business scheduling, etc. This policy aims to reduce the impact of impairments on the overall system and ensure rapid recovery after optical cable damage. Advanced impairments can threaten the core functions of the network, so flexible and efficient management and control policies are required. These policies ensure that data traffic can be effectively managed and the system will not crash even in the case of optical cable damage.

[0071] In one embodiment, the method comprises:

[0072] Real-time monitoring of whether the optical cable currently has abnormal parameters;

[0073] If there are no abnormal parameters in the optical cable, obtaining the frequency of change of the environmental data;

[0074] Determining whether to adjust the acquisition frequency parameter of the DVS sensor according to the change frequency of the environmental data;

[0075] When the change frequency of the environmental data is greater than a preset change threshold, it is determined that the condition for adjusting the acquisition frequency parameter of the DVS sensor is met;

[0076] Based on the judgment result, generating a collection frequency adjustment instruction;

[0077] The acquisition frequency adjustment instruction is sent to the DVS sensor to reduce the sensitivity of the DVS sensor when the high-frequency environment changes.

[0078] As mentioned above, the system first monitors the status of the optical cable to check whether there are any abnormalities, such as signal loss, increased loss, etc. By detecting optical cable problems early, the system can avoid being unable to respond in time when the optical cable fails. When the optical cable is normal, the system begins to pay attention to changes in the surrounding environment, especially the frequency of changes in environmental data (such as temperature, humidity, vibration, etc.). By monitoring the frequency of environmental changes, the system can determine whether there are drastic fluctuations in the external environment, which in turn affects the working settings of the sensor. If the frequency of environmental changes is high (such as frequent vibrations or temperature and humidity fluctuations), it will trigger the system to determine whether the acquisition frequency of the DVS sensor needs to be adjusted. The purpose of adjusting the acquisition frequency is to adapt to the characteristics of environmental changes and avoid generating too much redundant data due to rapid environmental changes. If the frequency of changes in environmental data is greater than the set threshold, it means that the environment fluctuates violently and the acquisition frequency of the sensor needs to be adjusted accordingly. In the case of frequent environmental changes, the system will adjust the acquisition frequency of the sensor to make it more adaptable to high-frequency changes. The system will generate adjustment instructions based on the frequency of changes in environmental data and send them to the DVS sensor to reduce its acquisition frequency to avoid the generation of redundant data. By reducing the acquisition frequency, the system avoids false alarms caused by excessive sensitivity and reduces unnecessary data processing burden. In a high-frequency changing environment, reducing the sensitivity of the sensor helps reduce excessive trigger signals and prevent the system from being disturbed by frequent environmental changes. By reducing the acquisition frequency and sensitivity, the system can effectively reduce redundant data and false alarms, thereby improving system stability and efficiency.

[0079] Reference Figure 3 In an embodiment of the present application, a DVS-based optical cable early warning system is also provided, including:

[0080] Receiving module 1, used for receiving brightness change data sent by the DVS sensor;

[0081] Identification module 2, used for analyzing the brightness change data, performing path identification on the brightness change data, and determining the target position of the brightness change data;

[0082] An acquisition module 3 is used to acquire environmental data of the target location and verify the brightness change data according to the environmental data;

[0083] A verification module 4, configured to analyze abnormal parameters of the target location when the target location meets an abnormal condition based on a verification result;

[0084] Prediction module 5, used for predicting abnormal change parameters of the target location according to the abnormal parameters of the target location;

[0085] The sending module 6 is used to determine a control strategy according to the abnormal parameters and the predicted abnormal change parameters, and based on the control strategy, generate warning information of the abnormal data of the target location and send it to the management end.

[0086] As described above, it can be understood that the various components of the DVS-based optical cable early warning system proposed in this application can realize the functions of any one of the DVS-based optical cable early warning management and control methods described above, and the specific structure will not be repeated.

[0087] Reference Figure 4 In the embodiment of the present application, a computer device is also provided. The computer device may be a server, and its internal structure may be as follows: Figure 4 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor designed by the computer is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data such as monitoring data. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a DVS-based optical cable early warning management and control method is implemented.

[0088] The above-mentioned processor executes the above-mentioned DVS-based optical cable early warning control method, including: when receiving brightness change data sent by the DVS sensor; parsing the brightness change data, performing path identification on the brightness change data, and determining the target position of the brightness change data; obtaining environmental data of the target position, and verifying the brightness change data according to the environmental data; based on the verification result, when the target position meets the abnormal condition, analyzing the abnormal parameters of the target position; based on the abnormal parameters of the target position, predicting the abnormal change parameters of the target position; determining a control strategy based on the abnormal parameters and the predicted abnormal change parameters, and based on the control strategy, generating early warning information for the abnormal data of the target position and sending it to the management end.

[0089] An embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, a DVS-based optical cable early warning control method is implemented, comprising the following steps: when brightness change data sent by a DVS sensor is received; parsing the brightness change data, performing path identification on the brightness change data, and determining a target position of the brightness change data; acquiring environmental data of the target position, and verifying the brightness change data according to the environmental data; based on a result of the verification, when the target position meets an abnormal condition, analyzing abnormal parameters of the target position; predicting abnormal change parameters of the target position according to the abnormal parameters of the target position; determining a control strategy according to the abnormal parameters and the predicted abnormal change parameters, and based on the control strategy, generating early warning information for the abnormal data of the target position and sending it to a management terminal.

[0090] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media provided in this application and used in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0091] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the existence of other identical elements in the process, device, article or method including the element.

[0092] The above description is only a preferred embodiment of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A DVS-based optical cable early warning control method, characterized in that: The method comprises: When receiving the brightness change data sent by the DVS sensor, parsing the brightness change data; Performing path identification on the brightness change data to determine a target position of the brightness change data; Acquire environmental data of the target location, and verify the brightness change data according to the environmental data; Based on the verification result, when the target position meets the abnormal condition, analyzing the abnormal parameters of the target position; According to the abnormal parameters of the target position, predicting the abnormal change parameters of the target position; Determine a control strategy according to the abnormal parameters and the predicted abnormal change parameters, and based on the control strategy, generate warning information of the abnormal data at the target location and send it to the management end; The verifying the brightness change data according to the environmental data includes: Acquire environmental data of the target location, combine the environmental data with the brightness change data, and verify whether the environmental data and the brightness change data match; When the generation of the brightness change data matches the environmental data, obtaining the change trends of the brightness change data and the environmental data within a preset time period; If the change trends of the brightness change data and the environmental data within the preset time period match, it is determined that the optical cable does not meet the warning condition; When the generation of the brightness change data does not match the environmental data, it is determined that the optical cable meets the warning condition.

2. The optical cable early warning control method based on DVS according to claim 1 is characterized in that: The combining the environment data and the brightness change data to verify whether the environment data and the brightness change data match includes: Acquiring the environmental data and brightness change data, wherein the environmental data includes weather parameters and environmental object parameters; Based on the time series, extract the change characteristics of the brightness change data, including the brightness change frequency and duration; extract the change characteristics of the environment data, including the environment change rate and duration; Calculate the correlation coefficient between the environmental data and the brightness change data; When the correlation coefficient is less than a preset coefficient threshold, it is determined that the generation of the brightness change data does not match the environmental data.

3. The optical cable early warning control method based on DVS according to claim 1 is characterized in that: The analyzing the abnormal parameters of the target position includes: According to the target position of the brightness change data, using infrared imaging to obtain temperature data of the target position; Perform layer overlap processing on the temperature data and the brightness change data to obtain images with the same spatial resolution as the temperature data and the brightness change data; Based on the result of the layer repainting process, the spatial resolution image is geometrically aligned and the heat accumulation area of ​​the temperature fluctuation is marked; Inputting the heat accumulation area into a preset pattern matching model, analyzing the optical cable damage type in the heat accumulation area through the pattern matching model, and outputting the analysis result, wherein the optical cable damage type includes cracks, local fractures or compression deformation; The abnormal parameters of the target position are determined according to the optical cable damage type.

4. The optical cable early warning control method based on DVS according to claim 3 is characterized in that: The step of predicting the abnormal change parameter of the target position according to the abnormal parameter of the target position includes: Obtaining historical data of the optical cable damage type and target location; Performing data analysis on the historical data of the optical cable damage type and the target location, and determining whether the optical cable damage type satisfies the damage extension law of the historical data; If the optical cable damage type does not satisfy the damage extension law of historical data, obtaining the optical cable structure parameters at the target location; The optical cable structural parameters and the optical cable damage type are used to simulate the propagation path, speed and final damage of the damage; According to the propagation path, speed and final damage of the simulated damage, the prediction of abnormal change parameters of the target location is completed.

5. The optical cable early warning control method based on DVS according to claim 1 is characterized in that: The determining of the control strategy according to the abnormal parameters and the predicted abnormal change parameters includes: Determining the damage level of the target location according to the abnormal parameters and the predicted abnormal change parameters; When the damage level of the target location is primary damage, analyzing the impact area of ​​the target location, determining a traffic scheduling path according to the impact area, the scheduling path is used to control the traffic to bypass the target location, and determining a primary damage control strategy based on the traffic scheduling path; When the damage level of the target location is high-level damage, identify whether the spare optical cable is occupied. If the spare optical cable is not occupied, transfer the traffic of the current damaged optical cable to the spare optical cable. If the spare optical cable is occupied, encrypt the traffic of the current damaged optical cable, and determine the management and control strategy of high-level damage based on the spare optical cable or traffic encryption.

6. The optical cable early warning control method based on DVS according to claim 1 is characterized in that: The method further comprises: Real-time monitoring of whether the optical cable currently has abnormal parameters; If there are no abnormal parameters in the optical cable, obtaining the frequency of change of the environmental data; Determining whether to adjust the acquisition frequency parameter of the DVS sensor according to the change frequency of the environmental data; When the change frequency of the environmental data is greater than a preset change threshold, it is determined that the condition for adjusting the acquisition frequency parameter of the DVS sensor is met; Based on the judgment result, generating a collection frequency adjustment instruction; The acquisition frequency adjustment instruction is sent to the DVS sensor to reduce the sensitivity of the DVS sensor when the high-frequency environment changes.

7. An optical cable early warning system based on DVS, used in the method according to any one of claims 1 to 6, characterized in that: include: A receiving module, configured to parse the brightness change data when receiving the brightness change data sent by the DVS sensor; An identification module, used to perform path identification on the brightness change data and determine a target position of the brightness change data; An acquisition module, used for acquiring environmental data of the target location, and verifying the brightness change data according to the environmental data; A verification module, configured to analyze abnormal parameters of the target location when the target location meets an abnormal condition based on a verification result; A prediction module, used for predicting abnormal change parameters of the target location according to the abnormal parameters of the target location; The sending module is used to determine a control strategy according to the abnormal parameters and the predicted abnormal change parameters, and based on the control strategy, generate warning information of the abnormal data of the target location and send it to the management end.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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