Optical cable cutover auxiliary method and device, computer equipment, readable storage medium and program product

Abstract

The invention relates to an optical cable cutover auxiliary method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: measuring temperature information of a to-be-cut optical cable on the optical cable distribution frame in real time by adopting temperature detection equipment positioned on the optical cable distribution frame; cooling the candidate optical cables at the to-be-cut-over position in sequence by adopting refrigeration equipment, and judging whether the temperature information is changed or not; the candidate optical cable represents an unknown optical cable including the to-be-cut optical cable; and under the condition that the temperature information changes, determining the candidate optical cable which is currently cooled as the to-be-cut optical cable. By adopting the method, the optical cable cutover efficiency can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of optical cable splicing, and in particular to an optical cable splicing auxiliary method, device, computer equipment, computer-readable storage medium and computer program product. Background Art

[0002] Optical cable splicing is a crucial operation in the construction, maintenance and optimization of communication networks, including the upgrading and reconstruction of optical cable lines, the access of new network nodes, equipment replacement or optical cable repair due to natural disasters and construction.

[0003] Currently, due to the aging, damage or loss of cable labels, it is difficult to quickly locate the target cable from a large number of cables during on-site splicing. Existing methods usually rely on red light recognition and cable identification. However, the detection distance of the red light recognition method is limited; when using traditional cable identification in a dense fiber environment, external optical signal interference may cause the recognition accuracy to decrease. These problems cause the splicing process to take a long time, affecting the service recovery speed and network operation stability, resulting in low splicing efficiency. Summary of the invention

[0004] Based on this, it is necessary to provide an optical cable splicing auxiliary method, device, computer equipment, computer readable storage medium and computer program product that can improve the efficiency of optical cable splicing in order to solve the above technical problems.

[0005] In a first aspect, the present application provides an optical cable cutover auxiliary method, comprising:

[0006] Using a temperature detection device located in an optical cable distribution frame to measure the temperature information of the optical cable to be spliced ​​on the optical cable distribution frame in real time;

[0007] Using refrigeration equipment, sequentially cooling candidate optical cables located at positions to be spliced, and determining whether the temperature information changes; the candidate optical cables represent unknown optical cables including the optical cables to be spliced;

[0008] In the case where the temperature information changes, the candidate optical cable currently being subjected to a temperature reduction process is determined as the optical cable to be spliced.

[0009] In one embodiment, the temperature detection device located in the optical cable distribution frame is used to measure the temperature information of the optical cable to be spliced ​​on the optical cable distribution frame in real time, including:

[0010] According to the optical cable connection node identifier of the optical cable to be spliced, identifying the optical cable to be spliced ​​on the optical cable distribution frame;

[0011] The temperature detection device is connected to any one of the optical cable cores in the optical cable to be spliced, so as to measure the temperature information of the optical cable to be spliced ​​in real time.

[0012] In one embodiment, before using a temperature detection device to perform temperature detection processing on the optical cable to be spliced ​​at the optical cable connection node position of the optical cable to be spliced ​​in real time, the method further includes:

[0013] Acquiring real-time service data and historical cutover data of the optical cable to be cutover;

[0014] Inputting the real-time service data and the historical cutover data into a pre-trained cutover impact prediction model to obtain a service impact prediction report for this optical cable cutover;

[0015] According to the service impact prediction report, the execution time of the optical cable cutover is generated, and the backup line of the optical cable cutover is determined.

[0016] In one embodiment, the obtaining of real-time service data and historical cutover data of the optical cable to be cutover includes:

[0017] Acquire real-time traffic distribution information, link status information, and associated service information of the optical cable to be cut, as well as current environment information;

[0018] Determining a service priority corresponding to the associated service information, and marking the associated service information with the service priority to obtain the marked associated service information;

[0019] The real-time traffic distribution information, the link status information, the marked associated service information and the current environment information are used as the real-time service data;

[0020] A historical cutover report recording a target cutover reason is queried from a historical database as the historical cutover data; the target cutover reason indicates a cutover reason of the optical cable to be cutover.

[0021] In one embodiment, determining the backup line for the current optical cable cutover includes:

[0022] Determine the cutover execution time according to the off-peak period information of the high-priority service in the service impact prediction report, and obtain the real-time performance data and historical stability scores of the candidate lines;

[0023] The backup line is determined from the candidate lines according to the cutover execution time, the real-time performance data and the historical stability score.

[0024] In one embodiment, after determining the backup line for the optical cable cutover, the method further includes:

[0025] generating a cutover task for the optical cable to be cutover according to the cutover execution time, and generating an optical cable routing map according to the optical cable information of the optical cable to be cutover;

[0026] The cutover task and the optical cable routing diagram are displayed to a target executor corresponding to the cutover task, and the task status of the cutover task is monitored and recorded in real time.

[0027] In one embodiment, the method further comprises:

[0028] Real-time monitoring of network performance information of the cutover line and the backup line corresponding to the optical cable to be cutover;

[0029] Dynamic switching of network services is performed between the cutover line and the backup line according to the network performance information.

[0030] In a second aspect, the present application also provides an optical cable splicing auxiliary device, comprising:

[0031] A temperature measurement module is used to measure the temperature information of the optical cable to be spliced ​​on the optical cable distribution frame in real time by using a temperature detection device located on the optical cable distribution frame;

[0032] A cooling processing module is used to use refrigeration equipment to sequentially cool candidate optical cables located at positions to be spliced, and determine whether the temperature information changes; the candidate optical cables represent unknown optical cables including the optical cables to be spliced;

[0033] The optical cable determination module is used to determine the candidate optical cable currently being subjected to temperature reduction treatment as the optical cable to be spliced ​​when the temperature information changes.

[0034] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0035] Using a temperature detection device located in an optical cable distribution frame to measure the temperature information of the optical cable to be spliced ​​on the optical cable distribution frame in real time;

[0036] Using refrigeration equipment, sequentially cooling candidate optical cables located at positions to be spliced, and determining whether the temperature information changes; the candidate optical cables represent unknown optical cables including the optical cables to be spliced;

[0037] In the case where the temperature information changes, the candidate optical cable currently being subjected to a temperature reduction process is determined as the optical cable to be spliced.

[0038] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0039] Using a temperature detection device located in an optical cable distribution frame to measure the temperature information of the optical cable to be spliced ​​on the optical cable distribution frame in real time;

[0040] Using refrigeration equipment, sequentially cooling candidate optical cables located at positions to be spliced, and determining whether the temperature information changes; the candidate optical cables represent unknown optical cables including the optical cables to be spliced;

[0041] In the case where the temperature information changes, the candidate optical cable currently being subjected to a temperature reduction process is determined as the optical cable to be spliced.

[0042] In a fifth aspect, the present application further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:

[0043] Using a temperature detection device located in an optical cable distribution frame to measure the temperature information of the optical cable to be spliced ​​on the optical cable distribution frame in real time;

[0044] Using refrigeration equipment, sequentially cooling candidate optical cables located at positions to be spliced, and determining whether the temperature information changes; the candidate optical cables represent unknown optical cables including the optical cables to be spliced;

[0045] In the case where the temperature information changes, the candidate optical cable currently being subjected to a temperature reduction process is determined as the optical cable to be spliced.

[0046] The optical cable splicing auxiliary method, device, computer equipment, computer-readable storage medium and computer program product described above firstly use a temperature detection device located in an optical cable distribution frame to measure the temperature information of the optical cable to be spliced ​​on the optical cable distribution frame in real time, provide accurate temperature data, and lay a foundation for locating the target optical cable through temperature changes in the subsequent process, and do not need to physically mark or disassemble the optical cable, thereby avoiding errors caused by manual intervention; then, use a refrigeration device to cool down the candidate optical cables located at the position to be spliced ​​in turn, and judge whether the temperature information has changed; the candidate optical cables represent unknown optical cables containing the optical cables to be spliced, and the temperature information of the candidate optical cables is determined by the temperature detection device. The target optical cable is subjected to detectable physical changes by cooling treatment, which significantly enhances the distinguishability of the candidate optical cable. In a dense optical cable environment, the unique temperature change characteristics of cooling are used to reduce the influence of external optical signal interference on the identification process, thereby not relying on optical cable labels and construction drawings, and improving the reliability of the positioning of the target optical cable. Finally, when the temperature information changes, the candidate optical cable currently being cooled is determined as the optical cable to be spliced, and the target optical cable is accurately located, and the confirmation process of the optical cable is quickly completed to avoid the risk of mis-cutting or missing cutting. Through automated temperature change detection, the time for optical cable identification is further shortened. In the above method, by combining the temperature detection equipment and the refrigeration equipment located in the optical cable distribution frame, the optical cable to be spliced ​​is quickly and accurately located, which significantly improves the efficiency and accuracy of optical cable splicing. At the same time, through the non-destructive detection method of temperature change characteristics, the limitations of the traditional method that relies on optical cable labels, red light recognition method or optical cable identification instrument are avoided, the risk of mis-cutting is reduced, and it is suitable for complex scenarios with dense optical cables or missing labels, which improves the reliability and applicability of the splicing task. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0048] Figure 1 A diagram of an application environment of an optical cable cutover auxiliary method in an embodiment;

[0049] Figure 2 A schematic diagram of a process flow of an optical cable cutover auxiliary method in one embodiment;

[0050] Figure 3 A schematic diagram of a flow chart of the execution time and backup line determination steps in one embodiment;

[0051] Figure 4 A schematic diagram of an optical cable splicing auxiliary system in one embodiment;

[0052] Figure 5 is a structural block diagram of an optical cable splicing auxiliary device in one embodiment;

[0053] Figure 6 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0054] 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.

[0055] The optical cable splicing auxiliary method provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. Among them, the terminal 102 communicates with the temperature detection device 104 located at the optical cable distribution frame and the refrigeration device 106 located at the position to be cut through the network. The terminal 102 first uses the temperature detection device 104 located at the optical cable distribution frame to measure the temperature information of the optical cable to be cut on the optical cable distribution frame in real time; then, the terminal 102 uses the refrigeration device 106 to cool down the candidate optical cables located at the position to be cut in turn, and judges whether the temperature information changes, wherein the candidate optical cable represents an unknown optical cable containing the optical cable to be cut; when the temperature information changes, the terminal 102 determines the candidate optical cable currently being cooled down as the optical cable to be cut. Among them, the terminal 102 can be but not limited to various personal computers, laptops, smart phones, tablet computers, etc. The terminal 102 can also be replaced by a server, which can be an independent physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0056] In an exemplary embodiment, Figure 2 As shown, a method for assisting optical cable splicing is provided, which is applied to Figure 1 The terminal 102 in the example is used as an example to illustrate, and the following steps are included:

[0057] Step S201: using a temperature detection device located in an optical cable distribution frame, measuring temperature information of an optical cable to be spliced ​​on the optical cable distribution frame in real time.

[0058] Among them, the optical cable distribution frame refers to a structured device used to manage and connect optical cables, usually located in a communication room or network access point, used to accommodate optical cables and their connection interfaces.

[0059] Temperature detection equipment refers to equipment that can monitor the temperature of optical cables in real time in a non-contact or distributed manner. It is often based on fiber Brillouin scattering (BOTDR, Brillouin Optical Time Domain Reflectometry) or Raman scattering (ROTDR, Raman Optical Time Domain Reflectometry) technology and has high-precision and wide-range monitoring capabilities.

[0060] The optical cable to be spliced ​​refers to the target optical cable to be cut and operated in this splicing task, and is usually included in multiple optical cables in an optical cable distribution frame.

[0061] Exemplarily, the terminal automatically starts the temperature detection device located in the optical cable distribution frame. After starting, the temperature detection device connects to a core optical fiber in the optical cable to be spliced, and measures the temperature information of the optical cable to be spliced ​​in real time with a periodic optical pulse signal. The terminal receives the output data of the temperature detection device, and uses the built-in temperature monitoring algorithm to analyze the measurement results to generate real-time temperature curve data of the optical cable to be spliced.

[0062] Step S202: using refrigeration equipment to sequentially cool the candidate optical cables located at the locations to be spliced, and determining whether the temperature information has changed.

[0063] The candidate optical cable refers to the unknown optical cable including the optical cable to be spliced. It refers to the set of all optical cables located in the location to be spliced ​​(such as the splicing construction site or optical cable well), which may include the optical cable to be spliced, but the target optical cable has not yet been determined.

[0064] Among them, refrigeration equipment refers to equipment that can cool down local areas of optical cables, usually including liquid nitrogen injectors, semiconductor refrigeration devices, etc., which are used to produce significant and detectable temperature changes.

[0065] Exemplarily, the terminal first activates the refrigeration equipment, and locates the refrigeration equipment to the candidate optical cable area in the optical cable well or construction site according to the task planning instructions. Subsequently, the terminal cools down the candidate optical cables in turn. During each cooling process, the refrigeration equipment automatically applies cooling to a single candidate optical cable in the target area, and the terminal obtains the temperature information of the optical cable to be spliced ​​in real time through linkage with the temperature detection equipment. During the cooling operation, the terminal compares the real-time collected temperature information with the baseline data according to the built-in temperature change judgment logic: if the temperature information changes significantly (such as the expected downward trend of the temperature curve), the terminal preliminarily confirms that the optical cable currently being cooled may be the optical cable to be spliced, and records the physical location of the optical cable. If the temperature information has not changed, the terminal instructs the refrigeration equipment to move to the next candidate optical cable and repeats the cooling and judgment operations.

[0066] Step S203: when the temperature information changes, the candidate optical cable currently being subjected to a temperature reduction process is determined as the optical cable to be spliced.

[0067] For example, when the terminal receives real-time data uploaded by the temperature detection device indicating that the temperature information of the current optical cable has changed significantly, the terminal directly marks it as an optical cable to be spliced ​​and performs the following operations:

[0068] Target optical cable confirmation: record the physical location information of the optical cable in the optical cable well or construction site (such as the optical cable number or arrangement position). Compare with the resource configuration data to verify whether the identification result is consistent with the target optical cable in the task plan. Cable identification report generation: record the location information of the optical cable to be cut, the temperature curve of the cooling treatment, and the confirmation time in the cutover task log. Generate an identification report for construction personnel to review and guide subsequent cutover operations. Exception handling mechanism: If the identification result is inconsistent with the task plan, a warning is triggered.

[0069] In the above-mentioned optical cable splicing auxiliary method, firstly, a temperature detection device located in an optical cable distribution frame is used to measure the temperature information of the optical cable to be spliced ​​on the optical cable distribution frame in real time, and accurate temperature data is provided, which lays a foundation for locating the target optical cable through temperature changes in the subsequent process, and there is no need to physically mark or disassemble the optical cable, thereby avoiding errors caused by manual intervention; then, a refrigeration device is used to cool down the candidate optical cables located at the position to be spliced ​​in turn, and it is judged whether the temperature information has changed; the candidate optical cable represents an unknown optical cable including the optical cable to be spliced, and a temperature change is applied to the target optical cable through the temperature reduction process. The physical changes detected significantly enhance the distinguishability of candidate optical cables, and in a dense optical cable environment, the unique temperature change characteristics of cooling are used to reduce the impact of external optical signal interference on the identification process, thereby not relying on optical cable labels and construction drawings, and improving the reliability of the target optical cable positioning; finally, when the temperature information changes, the candidate optical cable currently being cooled is determined as the optical cable to be spliced, and the target optical cable is accurately located, and the confirmation process of the optical cable is quickly completed to avoid the risk of mis-cutting or missing cutting. Through automated temperature change detection, the time for optical cable identification is further shortened. In the above method, by combining the temperature detection equipment and refrigeration equipment located in the optical cable distribution frame, the optical cable to be spliced ​​is quickly and accurately located, which significantly improves the efficiency and accuracy of optical cable splicing; at the same time, through the non-destructive detection method of temperature change characteristics, the limitations of the traditional method that relies on optical cable labels, red light recognition method or optical cable identification instrument are avoided, the risk of mis-cutting is reduced, and it is suitable for complex scenarios with dense optical cables or missing labels, which improves the reliability and applicability of splicing tasks.

[0070] In an exemplary embodiment, the above step S201 uses a temperature detection device located in the optical cable distribution frame to measure the temperature information of the optical cable to be spliced ​​on the optical cable distribution frame in real time, and also includes: identifying the optical cable to be spliced ​​on the optical cable distribution frame according to the optical cable connection node identifier of the optical cable to be spliced; connecting the temperature detection device to any optical cable core in the optical cable to be spliced ​​to measure the temperature information of the optical cable to be spliced ​​in real time.

[0071] The optical cable connection node identifier refers to the unique identifier used to mark the port location of the optical cable in the optical cable distribution frame, which is usually obtained through the resource management system or on-site label information. The optical cable to be spliced ​​is the target optical cable to be cut and operated in the splicing task, which is selected from the multiple optical cables in the optical cable distribution frame through the optical cable connection node identifier. Any optical fiber core refers to a single optical fiber channel in the optical cable to be spliced ​​that is used to connect the temperature detection equipment to collect temperature data.

[0072] Exemplarily, the terminal automatically extracts the optical cable connection node identifier of the optical cable to be cut from the resource management system according to the planning information of the cutover task. Through the matching process, the identifier is docked with the port resource on the optical cable distribution frame to locate the physical location of the target optical cable. After the target optical cable is identified, the temperature detection device is connected to an optical fiber core in the optical cable to be cut in the optical cable distribution frame. Subsequently, the temperature detection device starts the optical pulse signal, measures the temperature distribution data along the connected optical fiber core in real time, and uploads the temperature information to the terminal for real-time analysis.

[0073] In this embodiment, the optical cable connection node identifier is used to quickly locate the optical cable to be spliced, and the real-time temperature measurement is performed through direct connection with the optical fiber core, thereby realizing the accurate identification of the target optical cable and the automation of data collection, thereby improving the efficiency and accuracy of the optical cable splicing task. At the same time, the real-time collected temperature information provides a stable and reliable reference benchmark for the subsequent temperature reduction screening of candidate optical cables.

[0074] In an exemplary embodiment, Figure 3 As shown, in the above step S201, before using a temperature detection device to perform temperature detection processing on the optical cable to be spliced ​​in real time at the optical cable connection node position of the optical cable to be spliced, the following steps are also included:

[0075] Step S301, obtaining real-time service data and historical cutover data of the optical cable to be cutover;

[0076] Step S302, inputting the real-time service data and historical cutover data into a pre-trained cutover impact prediction model to obtain a service impact prediction report of the current optical cable cutover;

[0077] Step S303: generating the execution time of this optical cable cutover according to the service impact prediction report, and determining the backup line for this optical cable cutover.

[0078] Among them, real-time business data refers to the current network operation status information related to the optical cable to be cut, including real-time traffic distribution, link status and related business information, especially specific demand data for high-priority businesses.

[0079] Historical cutover data refers to historical records related to optical cables to be cutover or similar cutover tasks, including statistical results of the impact of the cutover operation on network performance and services.

[0080] The cutover impact prediction model is a pre-trained machine learning model that predicts and analyzes the scope, duration, and performance of backup paths of service interruptions that may be caused by the cutover task based on input data. Specifically, it is an intelligent analysis tool based on machine learning that is used to predict the potential impact of optical cable cutover tasks on networks and services. The model takes real-time service data and historical cutover data as input, where real-time data includes current traffic distribution, link status, and service priority information, and historical data covers service interruption scope, backup path performance, and recovery time. Through technologies such as time series prediction, classification model, and optimization model, the model can generate prediction results for service interruption scope and time, analyze the performance of backup paths, and provide cutover time window recommendations and comprehensive risk scores. The output results include the scope of service impact, protection strategies for high-priority services, backup path selection recommendations, etc., forming a business impact prediction report to guide the execution and optimization of cutover tasks. Through this model, the risk of service interruption can be significantly reduced, resource allocation can be optimized, refined decision-making can be supported, and the intelligence and efficiency of cutover tasks can be realized. The model can use time series prediction models (such as LSTM or Transformer) to analyze the traffic change trend and interruption duration before and after the cutover task, classification models (such as random forest or XGBoost) to evaluate the interruption risk and recovery time of services with different priorities, and optimization models (such as path optimization algorithms based on reinforcement learning) to recommend backup path switching strategies and resource allocation plans.

[0081] The service impact prediction report is the output of the model, which provides the impact of the cutover task on the current network service, recovery time prediction and optimization suggestions.

[0082] Exemplarily, the terminal obtains the real-time service data of the optical cable to be cut from the network management system and the resource management module, including the current traffic load, link status and priority of the related services of the optical cable. At the same time, the terminal accesses the historical database to extract the historical cutover data related to the optical cable to be cutover or similar tasks, and the data content includes the historical interruption time, the switching effect of the backup path and the recovery strategy of the high-priority service. Taking the above real-time data and historical data as input, the terminal calls the cutover impact prediction model for analysis and generates a business impact prediction report. The report content includes: the specific impact range and expected recovery time of the cutover on the high-priority service; the performance comparison of the current main route and the backup path, and the recommended switching strategy of the backup path; the score of the business interruption risk is used to guide the execution time of the cutover task. Afterwards, according to the business impact prediction report, the terminal can automatically generate the execution time of this optical cable cutover, giving priority to the off-peak period of high-priority services. At the same time, combined with the real-time performance data of the main route and the backup path, the terminal determines the best route that meets the business needs from multiple backup paths and records it in the cutover task plan.

[0083] In this embodiment, by combining real-time service data and historical cutover data, and using a pre-trained cutover impact prediction model, the potential impact on the network and services can be accurately assessed before the cutover task, thus achieving intelligent and refined task planning. The prediction report provides a scientific basis for decision-making on cutover time and backup lines, effectively reducing the risk of cutover tasks, while minimizing the impact of interruptions on high-priority services, and ensuring the overall stability and reliability of the network.

[0084] In an exemplary embodiment, the above-mentioned step S301 obtains the real-time business data and historical cutover data of the optical cable to be cutover, and also includes: obtaining the real-time traffic distribution information, link status information, and associated business information of the optical cable to be cutover, and obtaining the current environment information; determining the business priority corresponding to the associated business information, and marking the associated business information with the business priority to obtain the marked associated business information; using the real-time traffic distribution information, link status information, the marked associated business information and the current environment information as real-time business data; and querying from the historical database to obtain the historical cutover report that records the reason for the target cutover as the historical cutover data.

[0085] The target cutover reason indicates the cutover reason of the optical cable to be cutover.

[0086] Among them, real-time traffic distribution information refers to the network traffic data currently carried by the optical cable to be cut, including the traffic occupancy rate of the main route, traffic changes during peak hours, etc.; link status information refers to the current performance parameters of the optical cable, such as delay, jitter, and packet loss rate; associated business information refers to the business type, priority, service level agreement (SLA), etc. related to the optical cable to be cut; current environmental information refers to the external conditions at the cutover site, including weather conditions, accessibility of the optical cable well, and construction safety.

[0087] Exemplarily, the terminal can obtain the real-time traffic distribution information and link status information of the optical cable to be cut by connecting to the network management system. For example, the current traffic occupancy rate of the main route is 80%, and its peak traffic period is recorded as 8:00 to 12:00 every day. The current delay of the main route is 15ms, the jitter is 2ms, and the packet loss rate is 0.05%. The current delay of the backup path is 25ms, and the bandwidth utilization rate is 60%. The associated business information is extracted through the business management system, and the current environmental information is obtained from the environmental monitoring module, such as the weather is sunny, the temperature is 25℃, the optical cable well is free of water and is safe to reach, etc. Subsequently, the terminal prioritizes the business types in the associated business information in combination with the preset business priority rule table, such as marking the financial dedicated line as high priority, the enterprise dedicated line as medium priority, and the ordinary broadband as low priority, to form the marked associated business information. The terminal integrates the above information to generate real-time business data and uploads it to the task analysis module.

[0088] From the historical database, the terminal queries the relevant historical cutover reports according to the target cutover reasons of the optical cable to be cutover (such as optical cable upgrade, node migration, fault repair, etc.). The historical cutover reports include the service interruption scope, recovery time, backup path usage effect, abnormal situation records, etc. in the same type of cutover tasks. The terminal uses the queried historical cutover reports as historical cutover data for subsequent analysis. For example, the interruption scope of high-priority services in similar tasks is 10 users, and the interruption duration is 2 hours; the bandwidth utilization rate of the backup path has reached 95% in historical tasks, and there is a certain stability risk; in historical tasks, there is a delay of 5 minutes in the recovery of high-priority services when the backup path is switched; the average recovery time of ordinary services is 3 hours.

[0089] In this embodiment, by accurately acquiring real-time traffic distribution information, link status information, related business information and current environment information, and combining the query and integration of historical cutover data, a comprehensive and efficient data input is provided for the cutover impact prediction model, which helps to improve the intelligence and accuracy of cutover task planning, while effectively reducing the impact of cutover tasks on high-priority businesses.

[0090] In an exemplary embodiment, the above-mentioned step S303 determines the backup line for this optical cable cutover, and also includes: determining the cutover execution time based on the off-peak period information of the high-priority business in the business impact prediction report, and obtaining the real-time performance data and historical stability scores of the candidate lines; determining the backup line from the candidate lines based on the cutover execution time, real-time performance data and historical stability scores.

[0091] Among them, candidate lines refer to a set of backup paths for optical cables to be cut, including multiple alternative paths that meet network topology and bandwidth requirements; real-time performance data includes key indicators such as the current bandwidth utilization, latency, jitter and packet loss rate of candidate lines; historical stability scores are based on a comprehensive evaluation of the use of backup paths in historical tasks (such as failure rate, traffic change stability, etc.), and are used to measure the long-term reliability of candidate lines.

[0092] Exemplarily, the terminal extracts the off-peak period information of high-priority services from the service impact prediction report. For example, the report shows that the off-peak period of the financial dedicated line is from 1:00 to 5:00 a.m. every day, and there is no obvious off-peak demand for ordinary broadband services. Based on this, the terminal determines that the cutover execution time is 1:00 a.m. to minimize the impact on the financial dedicated line. Then, the terminal obtains the real-time performance data of the candidate lines through the real-time network monitoring module. For example: Candidate line A: The current bandwidth utilization is 60%, the delay is 20ms, the jitter is 3ms, and the packet loss rate is 0.05%; Candidate line B: The current bandwidth utilization is 40%, the delay is 15ms, the jitter is 2ms, and the packet loss rate is 0.02%; Candidate line C: The current bandwidth utilization is 80%, the delay is 25ms, the jitter is 5ms, and the packet loss rate is 0.1%. At the same time, the terminal extracts the historical stability score of the candidate line from the historical database. For example: Candidate line A: Score 8.5, stable operation in historical tasks, no significant fault records; Candidate line B: Score 9.2, excellent performance in historical tasks, almost no interruption records; Candidate line C: Score 7.0, insufficient bandwidth and high jitter problems in history; The terminal prioritizes the candidate lines through a comprehensive scoring algorithm based on the cutover execution time, real-time performance data and historical stability scores. For example: Candidate line B has the highest comprehensive score (based on the weighted calculation of real-time performance and historical scores) and is selected as the backup line for this optical cable cutover. Candidate line A is the secondary line and can be switched when problems occur in the primary backup path. Candidate line C is not selected due to its poor performance and historical stability. Finally, the terminal records the selected backup line information, including the path number, current performance data and stability score, and generates a backup line switching plan, which is uploaded to the task planning module to guide subsequent cutover operations.

[0093] In this embodiment, by combining the business impact forecast report, the off-peak period information of high-priority business, real-time performance data and historical stability scores, the optimal backup line is accurately screened, effectively reducing the impact of the cutover task on key business and ensuring the reliability and stability of the backup path during the cutover period. The accuracy of the cutover task planning is significantly improved, while the continuity of the network and business is guaranteed to the greatest extent.

[0094] In an exemplary embodiment, after the above step S303 determines the backup line for this optical cable cutover, it also includes: generating a cutover task for the optical cable to be cutover according to the cutover execution time, and generating an optical cable routing map according to the optical cable information of the optical cable to be cutover; displaying the cutover task and the optical cable routing map to the target executor corresponding to the cutover task, and monitoring and recording the task status of the cutover task in real time.

[0095] Among them, the cutover task refers to the specific plan formulated to complete the optical cable cutover operation, including the cutover time, operation steps, target optical cable and backup line information, etc.; the optical cable routing diagram is a graphical display generated based on the resource configuration data of the optical cable to be cutover, which is used to intuitively represent the optical cable path, main route and backup path and other information; the target executor refers to the operator assigned to the cutover task; the task status is the real-time progress information during the execution of the cutover task, including the task start time, completion time, step completion progress, etc.

[0096] For example, after determining the backup line, the terminal generates a cutover task plan according to the cutover execution time, including the following: Cutover time: start at 1:00 a.m., expected completion time is 3:00 a.m. Operation steps: switch the service to the backup line B; cutover the designated node of the optical cable; test the performance of the optical cable after cutover; restore the service to the main route. Target optical cable and backup line information: Optical cable to be cutover: No. 1001, the optical cable connection nodes are node A and node B; Backup line: Line B, with the highest comprehensive score and performance priority.

[0097] According to the cutover task plan, the terminal extracts the path data of the optical cable to be cutover from the resource management system and generates an optical cable routing map in combination with the backup line information. For example, the optical cable routing map shows the path of optical cable number 1001 and the network topology of its main route and backup path, indicating key nodes, connection ports, and optical cable length.

[0098] Afterwards, the terminal synchronizes the cutover task plan and optical cable routing diagram to the terminal device (such as mobile terminal or PC terminal) of the target executor. The executor can intuitively view the task time, operation steps, optical cable routing and backup path status through the terminal device to ensure a comprehensive understanding and preparation for the cutover task.

[0099] During the execution of the cutover task, the terminal monitors the task status in real time, including: Task start and progress update: The task start time is recorded as 1:00 am. After the cutover step is completed, the current step status is automatically marked as "completed" and the operation prompt for the next step is updated. Key node feedback: The optical cable performance test results recorded during the cutover process, such as optical loss data and signal attenuation. The time point and performance parameters of the test pass are recorded in the task log. Exception handling: If the cutover fails or the test fails, an alarm is sent to the target executor and management system in real time. The terminal provides corresponding remedial suggestions based on the backup task plan.

[0100] After the task is completed, the terminal generates a complete task status record, including the task start time, completion time, execution steps and optical cable performance test results, and archives it to the system database for subsequent query and analysis.

[0101] In this embodiment, by generating the cutover task and the optical cable routing diagram after determining the backup line, and monitoring and recording the task status in real time, not only the standardization and visualization of the cutover task is achieved, but also the execution personnel can grasp the task progress and abnormal situations in real time, which greatly improves the execution efficiency and accuracy of the task. This process significantly reduces the risk of misoperation or delay in the cutover process, and provides comprehensive guarantee for the smooth completion of the optical cable cutover task.

[0102] In an exemplary embodiment, the method further includes: real-time monitoring of network performance information of the cutover line and the backup line corresponding to the optical cable to be cutover; and dynamically switching network services between the cutover line and the backup line based on the network performance information.

[0103] The cutover line refers to the target line used to carry the original main route service after the optical cable cutover is completed; the backup line refers to the alternative line temporarily enabled during the cutover process to avoid service interruption. Dynamic switching processing refers to the automatic adjustment of service traffic between the cutover line and the backup line based on real-time monitoring results and network performance threshold rules to ensure the continuity and stable performance of network services.

[0104] For example, after the cutover task is completed, the terminal starts the network performance monitoring module to monitor the performance of the cutover line and the backup line in real time. The performance monitoring includes the following: performance data of the cutover line: bandwidth utilization is 70%, delay is 15ms, jitter is 2ms, and packet loss rate is 0.03%; performance data of the backup line: bandwidth utilization is 50%, delay is 20ms, jitter is 3ms, and packet loss rate is 0.05%.

[0105] The terminal analyzes the monitoring data in real time through the preset performance threshold rules. For example, if the performance of the line after cutover meets the business requirements, the bandwidth utilization is less than 80%, the delay is less than 20ms, and the packet loss rate is less than 0.1%, it can continue to be the main route. If the performance indicators of the line after cutover exceed the threshold (for example, the delay exceeds 30ms or the packet loss rate exceeds 0.1%), the terminal immediately triggers the dynamic switching mechanism to switch part or all of the business traffic to the backup line.

[0106] During the dynamic switching process, the terminal performs the following steps: Compare the performance data of the cutover line and the backup line in real time, and give priority to the line with better performance indicators. If the performance of the cutover line deteriorates and cannot meet the needs of high-priority services, the high-priority services will be switched to the backup line first, and the ordinary services can be switched later. The switching command is issued by the transmission network management module to realize the dynamic adjustment of network routing. The switching time, traffic distribution changes and business impact are recorded during the switching process. After the switching is completed, the terminal continues to monitor the line performance to ensure that the switched line can operate stably. If the performance of the backup line deteriorates after carrying the business, the terminal will try to restore the business to the cutover line or start other optimization strategies.

[0107] In this embodiment, the network performance information of the cutover line and the backup line is monitored in real time, and the service is dynamically switched based on the monitoring data, thereby ensuring the efficient operation of the network and the continuity of the service after the cutover. It not only effectively copes with the problem of line performance fluctuation after the cutover, but also minimizes the impact on high-priority services by dynamically adjusting service traffic, thereby improving the reliability and intelligence level of network operation.

[0108] In another exemplary embodiment, Figure 4 As shown, the present application provides an optical cable cutover auxiliary system, which includes: a cutover work order module, a resource management module, a transmission network management module, and an optical cable intelligent identification module.

[0109] The specific execution process of the optical cable cutover auxiliary system is as follows: 1. Through the cutover work order module, manage, coordinate and record the cutover tasks, and introduce an intelligent task allocation system to automatically allocate tasks based on historical data and current network status to ensure the reasonable allocation of personnel and resources. At the same time, set up real-time progress tracking and notification functions to ensure that the team is aware of the task status in a timely manner and that the cutover tasks are carried out in an orderly manner.

[0110] 2. Through the resource management module, a dynamic resource monitoring function is introduced. After receiving the cutover task, the involved optical cables and line information are automatically identified, and a visual optical fiber routing map is generated to facilitate quick confirmation and preparation of backup paths.

[0111] At the same time, a resource conflict warning mechanism is added to detect potential problems in advance, that is, through real-time monitoring of optical cable resources, backup paths, equipment status, personnel task allocation, network traffic load, and environmental conditions, potential conflicts that may affect the execution of the cutover task can be identified in advance. For example, optical cable ports or backup paths may be occupied by other tasks, which may cause conflicts. Insufficient equipment or overlapping tasks of executors may cause delays. Excessive network load or node capacity may affect traffic switching, and limited construction environment or bad weather may also affect the normal progress of tasks. This mechanism timely detects and prompts these conflicts through the linkage analysis of resource management system, network monitoring module and historical data, and provides suggestions for adjustment plans, such as reallocating tasks, adjusting execution time, optimizing backup paths or diverting traffic, etc., so as to ensure the smooth completion of the cutover task, effectively reduce the risk of business interruption and execution delay, and significantly improve the reliability and efficiency of tasks.

[0112] 3. Through the transmission network management module, a business impact assessment model based on machine learning is introduced to automatically analyze the potential impact of cutover on major customers and key businesses, and generate automated reports to facilitate collaborative communication with relevant departments and customers.

[0113] 4. Perform primary and backup route switching under the premise of ensuring business stability and backup line availability;

[0114] 5. Through the optical cable intelligent identification module, the physical intelligent cutover and performance evaluation of the main line optical cable are carried out. The process is as follows:

[0115] a. The distributed sensing module consists of a distributed temperature measurement module (BOTDR / ROTDR) and a distributed attenuation measurement module (OTDR, Optical Time Domain Reflectometry), which are placed on the ODF rack;

[0116] b. The distributed temperature detection module is connected to any core of the optical cable of the line to be cut;

[0117] c. Use the cooling module to cool down the optical cable by ∆𝑇, and observe the temperature curve in the distributed temperature measurement module. If the curve shows a temperature change, the optical cable is the target optical cable to be spliced. Otherwise, continue to use the cooling module to traverse all optical cables until the target optical cable is found and perform the splicing task;

[0118] d. After the cutover is completed, the distributed attenuation measurement module is connected to the main line optical cable after the cutover to test the loss and signal transmission of the new fusion point to ensure that the line quality meets the standard.

[0119] 6. After the cutover is completed, upload the cutover information, update the resource management module in real time, and automatically generate a cutover process report, including test results and fault feedback, to simplify the information entry process;

[0120] 7. Finally, through the transmission network management module, an intelligent recovery strategy is introduced to automatically decide whether to restore the service to the main route or keep it on the backup route based on the real-time network performance, ensuring the optimal recovery of the service under any circumstances.

[0121] In this embodiment, the intelligent task allocation system and dynamic resource monitoring function are introduced to make the management of the cutover task more efficient, optimize the allocation of personnel and resources, and reduce human intervention and errors; the resource management module improves the transparency of task execution by generating a visual fiber routing map and resource conflict warning, can quickly confirm and prepare backup paths, identify potential problems in advance, and reduce the risk of cutover; the transmission network management module uses machine learning models to automatically evaluate the impact of cutover on major customers and key businesses, help relevant departments and customers communicate effectively, reduce the risk of business interruption, and improve user satisfaction; the optical cable intelligent identification module uses distributed sensing technology to accurately locate the optical cable to be cut, and has the advantages of wide monitoring coverage, high real-time performance, and high monitoring accuracy, which effectively improves the efficiency of cutover. Multiple modules work together, and when the optical cable label is lost or inaccurate, the target optical cable can be quickly identified, which significantly improves the efficiency of cutover and reduces the risk of mistaken cuts, reduces operation and maintenance costs, and realizes the efficient management and execution of optical cable cutover tasks.

[0122] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0123] Based on the same inventive concept, the embodiment of the present application also provides an optical cable splicing auxiliary device for implementing the optical cable splicing auxiliary method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the embodiments of one or more optical cable splicing auxiliary devices provided below can refer to the limitations of the optical cable splicing auxiliary method above, and will not be repeated here.

[0124] In an exemplary embodiment, Figure 5As shown, an optical cable splicing auxiliary device is provided, comprising: a temperature measurement module 501, a temperature reduction processing module 502 and an optical cable determination module 503, wherein:

[0125] The temperature measurement module 501 is used to measure the temperature information of the optical cable to be spliced ​​on the optical cable distribution frame in real time by using the temperature detection equipment located on the optical cable distribution frame;

[0126] The cooling processing module 502 is used to use refrigeration equipment to sequentially cool the candidate optical cables located at the position to be cut, and determine whether the temperature information changes; the candidate optical cables represent unknown optical cables including the optical cables to be cut;

[0127] The optical cable determination module 503 is used to determine the candidate optical cable currently being subjected to a temperature reduction process as the optical cable to be spliced ​​when the temperature information changes.

[0128] In one of the embodiments, the temperature measurement module 501 is further used to identify the optical cable to be spliced ​​on the optical cable distribution frame according to the optical cable connection node identifier of the optical cable to be spliced; and connect the temperature detection device to any optical cable core in the optical cable to be spliced ​​to measure the temperature information of the optical cable to be spliced ​​in real time.

[0129] In one of the embodiments, the optical cable splicing auxiliary device further includes a splicing analysis module for obtaining real-time business data and historical splicing data of the optical cable to be spliced; inputting the real-time business data and historical splicing data into a pre-trained splicing impact prediction model to obtain a business impact prediction report of this optical cable splicing; generating the execution time of this optical cable splicing according to the business impact prediction report, and determining a backup line for this optical cable splicing.

[0130] In one of the embodiments, the above-mentioned cutover analysis module is also used to obtain real-time traffic distribution information, link status information, associated business information, and current environment information of the optical cable to be cutover; determine the business priority corresponding to the associated business information, and mark the associated business information with the business priority to obtain the marked associated business information; use the real-time traffic distribution information, link status information, marked associated business information and current environment information as real-time business data; query from the historical database to obtain a historical cutover report that records the target cutover reason as the historical cutover data; the target cutover reason indicates the cutover reason of the optical cable to be cutover.

[0131] In one of the embodiments, the above-mentioned cutover analysis module is also used to determine the cutover execution time according to the off-peak period information of the high-priority business in the business impact prediction report, and obtain the real-time performance data and historical stability scores of the candidate lines; determine the backup line from the candidate lines according to the cutover execution time, real-time performance data and historical stability scores.

[0132] In one of the embodiments, the optical cable cutover auxiliary device is further used to generate a cutover task for the optical cable to be cutover according to the cutover execution time, and to generate an optical cable routing map according to the optical cable information of the optical cable to be cutover; to display the cutover task and the optical cable routing map to the target executor corresponding to the cutover task, and to monitor and record the task status of the cutover task in real time.

[0133] In one of the embodiments, the optical cable cutover auxiliary device is further used to monitor in real time the network performance information of the cutover line and the backup line corresponding to the optical cable to be cutover; and dynamically switch the network service between the cutover line and the backup line based on the network performance information.

[0134] Each module in the above optical cable splicing auxiliary device can be implemented in whole or in part by software, hardware or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each module.

[0135] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 6 As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input / output interface. The processor of the computer device 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 and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, near field communication (NFC) or other technologies. When the computer program is executed by the processor, an optical cable cutting auxiliary method is implemented. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0136] Those skilled in the art will understand that Figure 6 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0137] In one embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiments when executing the computer program.

[0138] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0139] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0140] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0141] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed 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 the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0142] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0143] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. An optical cable cutover auxiliary method, characterized in that: The method comprises: Using a temperature detection device located in an optical cable distribution frame to measure the temperature information of the optical cable to be spliced ​​on the optical cable distribution frame in real time; Using refrigeration equipment, sequentially cooling candidate optical cables located at positions to be spliced, and determining whether the temperature information changes; the candidate optical cables represent unknown optical cables including the optical cables to be spliced; In the case where the temperature information changes, the candidate optical cable currently being subjected to a temperature reduction process is determined as the optical cable to be spliced.

2. The method according to claim 1, characterized in that The method uses a temperature detection device located on the optical cable distribution frame to measure the temperature information of the optical cable to be spliced ​​on the optical cable distribution frame in real time, including: According to the optical cable connection node identifier of the optical cable to be spliced, identifying the optical cable to be spliced ​​on the optical cable distribution frame; The temperature detection device is connected to any one of the optical cable cores in the optical cable to be spliced, so as to measure the temperature information of the optical cable to be spliced ​​in real time.

3. The method according to claim 1, characterized in that Before using the temperature detection device to perform temperature detection processing on the optical cable to be spliced ​​at the optical cable connection node position of the optical cable to be spliced ​​in real time, the method also includes: Acquiring real-time service data and historical cutover data of the optical cable to be cutover; Inputting the real-time service data and the historical cutover data into a pre-trained cutover impact prediction model to obtain a service impact prediction report for this optical cable cutover; According to the service impact prediction report, the execution time of the optical cable cutover is generated, and the backup line of the optical cable cutover is determined.

4. The method according to claim 3, characterized in that The obtaining of real-time service data and historical cutover data of the optical cable to be cutover includes: Acquire real-time traffic distribution information, link status information, and associated service information of the optical cable to be spliced, as well as current environment information; Determining a service priority corresponding to the associated service information, and marking the associated service information with the service priority to obtain the marked associated service information; The real-time traffic distribution information, the link status information, the marked associated service information and the current environment information are used as the real-time service data; A historical cutover report recording a target cutover reason is queried from a historical database as the historical cutover data; the target cutover reason indicates a cutover reason of the optical cable to be cutover.

5. The method according to claim 3, characterized in that: The step of determining the backup line for the current optical cable cutover includes: Determine the cutover execution time according to the off-peak period information of the high-priority service in the service impact prediction report, and obtain the real-time performance data and historical stability scores of the candidate lines; The backup line is determined from the candidate lines according to the cutover execution time, the real-time performance data and the historical stability score.

6. The method according to claim 5, characterized in that After determining the backup line for the optical cable cutover, the method further includes: generating a cutover task for the optical cable to be cutover according to the cutover execution time, and generating an optical cable routing map according to the optical cable information of the optical cable to be cutover; The cutover task and the optical cable routing diagram are displayed to a target executor corresponding to the cutover task, and the task status of the cutover task is monitored and recorded in real time.

7. The method according to claim 6, characterized in that The method further comprises: Real-time monitoring of network performance information of the cutover line and the backup line corresponding to the optical cable to be cutover; Dynamic switching of network services is performed between the cutover line and the backup line according to the network performance information.

8. An optical cable splicing auxiliary device, characterized in that: The device comprises: A temperature measurement module is used to measure the temperature information of the optical cable to be spliced ​​on the optical cable distribution frame in real time by using a temperature detection device located on the optical cable distribution frame; A cooling processing module is used to use refrigeration equipment to sequentially cool candidate optical cables located at positions to be spliced, and determine whether the temperature information changes; the candidate optical cables represent unknown optical cables including the optical cables to be spliced; The optical cable determination module is used to determine the candidate optical cable currently being subjected to temperature reduction treatment as the optical cable to be spliced ​​when the temperature information changes.

9. 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 7 are implemented.

10. 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 7 are implemented.

11. A computer program product, comprising a computer program, 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 7 are implemented.

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