Cable line operation method and device, storage medium, processor and program product

Abstract

The invention discloses a cable line operation method and device, a storage medium, a processor and a program product. The method comprises the following steps: determining an operation state of a cable line; in response to the fact that the operation state is the abnormal operation state, multiple operation strategies of the cable line are determined, and the operation strategies are used for representing rules for operating the cable line; simulating response results of the cable line under the plurality of operation strategies by using the digital twinborn model of the cable line to obtain a plurality of response results; determining a target operation strategy from a plurality of operation strategies based on the plurality of response results; and operating the cable line according to the target operation strategy. According to the invention, the technical problem of low maintenance efficiency of the operation state of the cable line is solved.

Description

Technical Field

[0001] The present application relates to the field of power systems, and in particular to a method, device, storage medium, processor and program product for operating a cable line. Background Art

[0002] Cable lines are an important part of power transmission and distribution systems. However, during long-term operation, cable lines are affected by various internal and external factors, which lead to abnormal conditions and failures in cable lines.

[0003] In the related technologies, the monitoring and diagnosis of cable lines usually only rely on acoustic three-dimensional scanning technology and multi-path propagation effect analysis methods. However, the above methods are limited by the resolution of the equipment and the complexity of the algorithm, which makes it difficult to capture the details of the internal structure of the cable accurately, resulting in a technical problem of low efficiency in maintaining the operating status of the cable lines.

[0004] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0005] The embodiments of the present application provide a method, device, storage medium, processor and program product for operating a cable line, so as to at least solve the technical problem of low efficiency in maintaining the operating status of the cable line.

[0006] According to one aspect of an embodiment of the present application, a method for operating a cable line is provided, which may include: determining the operating status of the cable line; in response to the operating status being an abnormal operating status, determining multiple operating strategies for the cable line, wherein the operating strategies are used to represent the rules for operating the cable line; using a digital twin model of the cable line, simulating the response results of the cable line under multiple operating strategies respectively, and obtaining multiple response results; based on the multiple response results, determining a target operating strategy from the multiple operating strategies; and operating the cable line according to the target operating strategy.

[0007] Optionally, determining the operating status of the cable line includes: collecting operating data of the cable line; and determining the operating status based on the operating data.

[0008] Optionally, determining the operating status based on the operating data includes: constructing a dynamic model of the cable line based on the operating data, wherein the dynamic model is used to characterize changes in the operating status of the cable line under multiple operating data; monitoring the dynamic model in real time to obtain monitoring results; and determining the operating status based on the monitoring results.

[0009] Optionally, constructing a dynamic model of the cable line based on the operating data includes: constructing a dynamic model based on cable operating status data in the operating data, wherein the cable operating status data is at least used to characterize electrical characteristics of the cable line.

[0010] Optionally, the method may also include: constructing a three-dimensional cable structure of the cable line based on the operating data, wherein the three-dimensional cable structure is at least used to characterize the geometric shape of the cable line; and constructing a digital twin model based on the three-dimensional cable structure and the dynamic model.

[0011] Optionally, based on the operating data, a three-dimensional cable structure of the cable line is constructed, including: determining the acoustic signal characteristics of the acoustic pulse sensor signal in the operating data; extracting the acoustic signal characteristics to obtain the propagation delay of the acoustic pulse sensor signal; determining the path propagation effect data of the acoustic pulse sensor signal based on the propagation delay and the acoustic propagation path of the acoustic pulse sensor signal; and constructing the three-dimensional cable structure based on the path propagation effect data.

[0012] Optionally, based on the path propagation effect data, a three-dimensional cable structure is constructed, including: dividing the cable line according to the geometric shape and material properties of the cable line to obtain at least one divided area; separating the path propagation effect data according to the at least one divided area to obtain regional data corresponding to the at least one divided area; converting the path propagation effect data into an acoustic wave propagation trajectory of an acoustic wave pulse sensing signal; and constructing the three-dimensional cable structure based on the acoustic wave propagation trajectory and the regional data.

[0013] Optionally, collecting operation data of the cable line includes: acquiring operation data collected by a distributed optical fiber sensing system and / or a discharge detection device.

[0014] Optionally, in response to the operating state being an abnormal operating state, multiple operating strategies for the cable line are determined, including: in response to the operating state being an abnormal operating state, using a state recognition model to identify abnormal operating data in the abnormal operating state to obtain the abnormal cause of the operating state, wherein the state recognition model is trained based on historical abnormal operating data of the cable line; and determining multiple operating strategies corresponding to the abnormal causes.

[0015] According to another aspect of an embodiment of the present application, a cable line operation device is also provided, which may include: a first determination unit, used to determine the operating status of the cable line; a second determination unit, used to determine multiple operating strategies of the cable line in response to the operating status being an abnormal operating status, wherein the operating strategy is used to represent the rules for operating the cable line; a simulation unit, used to use a digital twin model of the cable line to simulate the response results of the cable line under multiple operating strategies respectively, and obtain multiple response results; a third determination unit, used to determine a target operating strategy from multiple operating strategies based on multiple response results; and an operating unit, used to operate the cable line according to the target operating strategy.

[0016] According to another aspect of an embodiment of the present application, a computer-readable storage medium is also provided, which includes a stored program, wherein when the program is running, the device where the computer-readable storage medium is located is controlled to execute the cable line operation method of the embodiment of the present application.

[0017] According to another aspect of an embodiment of the present application, a processor is further provided, the processor being used to run a program, wherein when the program is run by the processor, the cable line operation method of the embodiment of the present application is executed.

[0018] According to another aspect of an embodiment of the present application, a program product is also provided, the program product comprising computer instructions, wherein the computer instructions, when executed by a processor, implement the operation method of the cable line of the embodiment of the present application.

[0019] In an embodiment of the present application, the operating state of the cable line is determined; in response to the operating state being an abnormal operating state, multiple operating strategies of the cable line are determined, wherein the operating strategy is used to represent the rules for operating the cable line; using the digital twin model of the cable line, the response results of the cable line under multiple operating strategies are simulated to obtain multiple response results; based on the multiple response results, a target operating strategy is determined from multiple operating strategies; and the cable line is operated according to the target operating strategy. That is to say, this embodiment determines the operating state of the cable line. If the operating state of the cable line is an abnormal operating state, multiple operating strategies (that is, maintenance strategies) for maintaining the high-voltage cable line can be determined. Using the digital twin model, the most suitable target operating strategy in the operating strategy can be determined, and the cable line is maintained according to the target operating strategy, thereby achieving the technical effect of improving the maintenance efficiency of the operating state of the cable line, and solving the technical problem of low efficiency in maintaining the operating state of the cable line. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0021] Figure 1 is a flow chart of a method for operating a cable line according to an embodiment of the present application;

[0022] Figure 2 is a schematic diagram of an operation and decision-making system according to an embodiment of the present application;

[0023] Figure 3 is a schematic diagram of an operating device of a cable line according to an embodiment of the present application;

[0024] Figure 4 is a structural block diagram of a computer terminal according to an embodiment of the present application;

[0025] Figure 5 It is a block diagram of an electronic device for a cable line operation method according to an embodiment of the present application. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0027] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0028] According to an embodiment of the present application, an embodiment of a method for operating a cable line is provided, and the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and, although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0029] In this embodiment, a cable line operation method is proposed. The method can determine the operating status of the cable line. If the operating status of the cable line is an abnormal operating status, multiple operating strategies (i.e., maintenance strategies) for maintaining the high-voltage cable line can be determined. By using a digital twin model, the most suitable target operating strategy among the operating strategies can be determined, and the cable line can be maintained according to the target operating strategy, thereby achieving the technical effect of improving the maintenance efficiency of the cable line operating status and solving the technical problem of low efficiency in maintaining the operating status of the cable line.

[0030] Figure 1 FIG. 1 is a flow chart of a method for operating a cable line according to an embodiment of the present application. Figure 1 As shown, the method may include the following steps:

[0031] Step S102, determining the operating status of the cable line.

[0032] In the technical solution provided in step S102 of the present application, the cable line may be a high-voltage cable line, which may be an important component of the power transmission and distribution system, and may be used to ensure the safe operation of power equipment and personal safety. The operating state may include an abnormal operating state and a normal operating state.

[0033] Optionally, operation data of the cable line during operation may be acquired, and the operation status of the cable line may be determined based on the operation data.

[0034] Step S104, in response to the operating state being an abnormal operating state, determining a plurality of operating strategies for the cable line, wherein the operating strategy is used to represent a rule for operating the cable line.

[0035] In the technical solution provided in the above step S104 of the present application, if the operating state is an abnormal operating state, the cable line needs to be maintained. Therefore, in response to the operating state being an abnormal operating state, multiple operating strategies for the cable line can be determined.

[0036] Optionally, the above operation strategy can be an operation and maintenance decision plan for maintaining the cable line, which can be used to represent the rules for operating the cable line, and can refer to an action plan formulated to ensure the normal operation of the high-voltage cable line and extend its service life based on the cable abnormal state diagnosis results and the response changes of the digital twin model, which can include but are not limited to the following types: preventive maintenance, emergency repair, emergency repair, material replacement or upgrade and system optimization, etc. For example, it can be to replace the aging cable segment, strengthen the sealing of the cable joint, or adjust the load distribution of the cable to reduce local overheating, or to close the cable line segment affected by the fault. For example, it can be a strategy for adjusting the operating parameters of the cable line, such as voltage, current or load. It should be noted that the above is only an example, and the operation strategy can be selected according to the type of abnormal operation state, and can be a pre-set strategy. There is no specific restriction on the type of operation strategy here.

[0037] Optionally, operating strategies corresponding to different operating states can be set in advance. When the operating state is an abnormal operating state, multiple operating strategies can be selected from the pre-set operating strategies, or when the operating state is determined to be an abnormal operating state, different operating strategies can be set according to the current operating state.

[0038] For example, the cable line has abnormal temperature under a certain load, so that the operation state of the cable line is abnormal. The operation strategy of the cable line can be determined as: reducing the load of the cable line and / or increasing the working efficiency of the cooling system of the cable line.

[0039] Step S106, using the digital twin model of the cable line, simulate the response results of the cable line under multiple operation strategies to obtain multiple response results.

[0040] In the technical solution provided in step S106 of the present application, the digital twin model can be used to simulate the response results of the cable line under different operation strategies, and can be a virtual model that can be used to simulate the behavior of the entity (cable line) to determine the response result. The response result can be the operation result under the operation strategy, which can be used to characterize the response change result, and can be expressed by R response express.

[0041] Optionally, a digital twin model of the cable line can be constructed in advance to determine multiple operating strategies for the cable line. The digital twin model can be used to model the multiple operating strategies separately to determine the response results of the cable line under different operating strategies and obtain multiple response results.

[0042] Step S108: determining a target operation strategy from multiple operation strategies based on the multiple response results.

[0043] In the technical solution provided in the above step S108 of the present application, based on the response result, the best performing or most suitable operating strategy among multiple operating strategies can be determined, and the operating strategy can be determined as the target operating strategy.

[0044] Optionally, by building a digital twin model and combining it with real-time data, dynamic monitoring of the cable line can be achieved, the operating status and potential risks of the cable can be reflected in a timely manner, and a scientific and reasonable target operation strategy can be determined based on the response results obtained from the simulation.

[0045] Step S110, operating the cable line according to the target operation strategy.

[0046] In the technical solution provided in the above step S110 of the present application, the cable line is maintained according to the target operation strategy.

[0047] Optionally, the response results of the cable line under different operation strategies are obtained, and the response results can be used to characterize the operation status of the cable line under different operation strategies. Feedback data corresponding to multiple response results can be obtained, and the feedback data can be used to characterize the response status of the response results and the user's evaluation of the response results. The feedback data of multiple operation strategies can be used to determine the target operation strategy from the multiple operation strategies. Further, the cable line can be operated according to the target operation strategy.

[0048] Optionally, by continuously collecting and analyzing feedback data generated when executing decision-making plans, the system can further adjust the digital twin model to make future decisions more accurate and effective, thereby significantly improving the operation and maintenance level of high-voltage cable lines.

[0049] Through the above steps S102 and S110 of the present application, the operating state of the cable line is determined; in response to the operating state being an abnormal operating state, multiple operating strategies of the cable line are determined, wherein the operating strategy is used to represent the rules for operating the cable line; using the digital twin model of the cable line, the response results of the cable line under multiple operating strategies are simulated to obtain multiple response results; based on the multiple response results, the target operating strategy is determined from multiple operating strategies; according to the target operating strategy, the cable line is operated. That is to say, this embodiment determines the operating state of the cable line. If the operating state of the cable line is an abnormal operating state, multiple operating strategies (that is, maintenance strategies) for maintaining the high-voltage cable line can be determined. Using the digital twin model, the most suitable target operating strategy in the operating strategy can be determined, and the cable line is maintained according to the target operating strategy, so as to achieve the technical effect of improving the maintenance efficiency of the operating state of the cable line, and solve the technical problem of low efficiency in maintaining the operating state of the cable line.

[0050] The above method of this embodiment is further introduced below.

[0051] As an optional implementation, step S102, determining the operating status of the cable line, includes: collecting operating data of the cable line; and determining the operating status based on the operating data.

[0052] In this embodiment, the operation data of the cable line can be collected, and the operation status of the cable line can be determined based on the operation data. The above operation data can be high-voltage cable data, which can be used to characterize the operation status of the high-voltage cable line, for example, it can be a sonic pulse sensing signal; it can be optical fiber sensing data such as the temperature and stress state of the cable monitored by optical fiber sensing technology; it can be local discharge data collected by local discharge monitoring equipment; or it can be grounding system monitoring data such as real-time resistance and temperature data of the cable grounding node obtained by the grounding resistance online monitoring system; or it can be external temperature environment data of the cable line. It should be noted that this is only an example, and there is no specific restriction on the type of operation data.

[0053] Optionally, the operation data of the cable line can be collected through the data acquisition module, and the operation status of the cable line can be determined based on the operation data. The above-mentioned data acquisition module can be a variety of sensors or monitoring devices, for example, it can be an ammeter, a voltmeter, a temperature acquisition device, etc. It should be noted that this is only for example description, and there is no specific limitation on the type of data acquisition device.

[0054] Optionally, the original multimodal data of the high-voltage cable line is collected, and the original multimodal data can be preprocessed to obtain high-voltage cable data, which can at least include an acoustic pulse sensor signal and cable operation status data, and the operation status can be determined based on the high-voltage cable data. The preprocessing can be a processing method such as data cleaning, supplementation, and conversion, and the preprocessing method is not specifically limited here.

[0055] The method for determining the operating status based on the operating data is further described below.

[0056] As an optional implementation, determining the operating status based on the operating data includes: constructing a dynamic model of the cable line based on the operating data, wherein the dynamic model is used to characterize the changes in the operating status of the cable line under multiple operating data; monitoring the dynamic model in real time to obtain monitoring results; and determining the operating status based on the monitoring results.

[0057] In this embodiment, a dynamic model of the cable line can be constructed based on the operating data. The dynamic model can be a cable operating state dynamic model, which can be used to characterize the operating state of the cable line under different operating data. Therefore, the dynamic model can be used to reflect the change in the motion state of the cable line under multiple operating data. Furthermore, by real-time monitoring of the dynamic model, a monitoring result can be obtained, and the operating state can be determined based on the monitoring result. Among them, the above monitoring results can be used to determine whether the operating state is an abnormal operating state or a normal operating state. For example, if the monitoring result shows that the current of the cable line exceeds the current threshold 5 times within one hour, it can be determined that the operating state of the cable line at this time is an abnormal operating state. It should be noted that the above method for determining the operating state based on the monitoring results is only an example, and no specific limitation is made here.

[0058] Optionally, based on the operating data, a dynamic model of the cable line can be constructed, and the conditions of the dynamic model under different operating data can be monitored to obtain monitoring results. Based on the monitoring results at multiple times, the operating status of the cable line can be determined.

[0059] Optionally, based on the operating data, a dynamic model of the cable operating status of the cable line can be constructed, and the cable operating status dynamic model can be monitored in real time to obtain monitoring results. When the operating status of the cable line is an abnormal operating status, the monitoring results can include cable abnormal status data. Therefore, by judging the monitoring results, the operating status of the cable line at this time can be determined.

[0060] As an optional implementation, a dynamic model of a cable line is constructed based on the operation data, including: constructing a dynamic model based on cable operation status data in the operation data, wherein the cable operation status data is at least used to characterize the electrical characteristics of the cable line.

[0061] In this embodiment, the above-mentioned cable operation status data may include optical fiber sensing data, partial discharge data and grounding system monitoring data. The above-mentioned optical fiber sensing data may include at least cable temperature and stress state. By deploying a distributed optical fiber sensing system, the cable temperature and stress state can be monitored in real time. The above-mentioned partial discharge data may include cable body partial discharge signals, cable joint partial discharge signals and cable terminal partial discharge signals. By using a partial discharge detection device, the cable body partial discharge signals, cable joint partial discharge signals and cable terminal partial discharge signals can be monitored. The above-mentioned grounding system monitoring data may include real-time resistance and temperature data of the cable grounding node. By using a grounding resistance online monitoring system, the real-time resistance and temperature data of the grounding node are collected. Optionally, by deploying a distributed optical fiber sensing system, the temperature and stress state of the cable can be monitored in real time, thereby obtaining dynamic information of the cable operation in a timely manner, and using a partial discharge detection device to monitor the partial discharge signals of the cable body, joints and terminals, thereby enhancing the early identification and accurate diagnosis capabilities of cable faults. By collecting grounding system monitoring data in real time, the resistance and temperature status of the cable grounding nodes can be monitored, which improves the safety and reliability of the cable lines. By integrating optical fiber sensing data, partial discharge data and grounding system monitoring data, comprehensive cable operation status data is formed, providing a data basis for subsequent abnormal status identification and decision-making.

[0062] Optionally, a cable operation status dynamic model may be established based on the cable operation status data, wherein the cable operation status data may at least be used to characterize the electrical characteristics of the cable line.

[0063] Optionally, the following calculation formula can be used to characterize the cable operation status dynamic model:

[0064]

[0065]

[0066]

[0067] in, can be used to characterize the state variable vector, u(t) can be used to characterize the input variable vector, and f(·) can be used to characterize the state transfer function. can be used to characterize the observation vector, h(·) can be used to characterize the observation function, Q new Can be used to characterize the updated cable operation status, Q old It can be used to characterize the cable operation status before the update.

[0068] For example, the process of establishing a cable operation state dynamic model based on cable operation state data involves understanding and simulating the dynamic behavior of the cable under different operating conditions, which may include the following steps: Collecting the operation state data of the high-voltage cable line, such as optical fiber sensing data (including temperature and stress state), partial discharge data (partial discharge signals of the cable body, joints and terminals), and grounding system monitoring data (real-time resistance and temperature data). Determine the key variables that can describe the cable operation state in the cable operation state data, such as cable temperature, stress, partial discharge intensity, grounding resistance and temperature. The above variables can be used as state variables of the cable operation state dynamic model to track the changes in the cable operation state. Identify external input variables that affect the cable operation state, such as ambient temperature, load current, external mechanical stress, etc. The above variables can be used as input variables of the cable operation state dynamic model to simulate different operating conditions. Based on physical principles or historical data, a state transfer function can be constructed, which can be used to describe how the cable operation state variables change over time and with changes in external input variables. For example, the temperature of the cable may depend on the ambient temperature and load current, while the stress may be affected by the physical structure of the cable and external mechanical stress. An observation function is defined, which can be used to compare the predicted state of the cable operation status dynamic model with the actual observed data. Furthermore, the model can be trained using historical data sets, and the difference between the predicted state and the actual observed state can be minimized by adjusting the model parameters. The training process may involve the use of machine learning algorithms, such as regression or neural networks, to optimize the state transfer function and the observation function. An online model update mechanism can be established to dynamically adjust the cable operation status using new observation data to ensure that the model can adapt to changes in the cable operation environment and improve the accuracy of fault diagnosis and maintenance decisions. The established cable operation status dynamic model can be applied to the real-time monitoring system, continuously collect operation data, and adjust the model parameters based on actual feedback to improve the model's prediction accuracy and the effectiveness of decision-making.

[0069] Optionally, the cable operation status dynamic model can monitor the cable operation status in real time (for example, the health of the cable line, predict potential faults, etc.), and based on this information, the operation and maintenance decision plan can be further determined. Through the above steps, a dynamic model that can reflect the changes in the internal structure and operation status of the cable can be constructed, providing strong support for the intelligent operation and maintenance of the cable.

[0070] It should be noted that the above-mentioned method of constructing a dynamic model based on cable operation status data is only an example. As long as the dynamic model is constructed based on cable operation status data, it should be within the protection scope of this application and no specific restrictions are made here.

[0071] In this embodiment, by combining the state variable vector and the input variable vector, the changes in the operating state of the cable are monitored in real time, reflecting the performance of the cable under different working conditions. The state transfer function is used to effectively describe the changing law of the cable operating state, help analyze the response of the cable under different input conditions, and enhance the understanding of the cable behavior. At the same time, through the application of the observation vector and the observation function, the actual measurement data can be compared with the model prediction. Through the state update mechanism included in the cable operating state dynamic model, the operating state of the cable is dynamically adjusted according to the new observation data to ensure that the model always reflects the latest state of the cable, thereby improving the timeliness of fault diagnosis and maintenance decisions.

[0072] As an optional implementation, the method may also include: constructing a three-dimensional cable structure of the cable line based on the operating data, wherein the three-dimensional cable structure is at least used to characterize the geometric shape of the cable line; and constructing a digital twin model based on the three-dimensional cable structure and the dynamic model.

[0073] In this embodiment, before using the digital twin model of the cable line to simulate the response results of the cable line under multiple operation strategies, the digital twin model can be constructed by the following steps: based on the operation data, the cable three-dimensional structure of the cable line can be constructed, and based on the cable three-dimensional structure and the dynamic model, the digital twin model can be constructed. The three-dimensional cable structure can at least be used to characterize the collective shape of the cable line.

[0074] Optionally, based on the cable three-dimensional structure (which can be a cable three-dimensional structure model) and the cable operating status model, a digital twin model of the high-voltage cable line can be constructed. The digital twin model can simulate the response change results (i.e., response results) of the cable in different cable operating states.

[0075] Optionally, the digital twin model of the high-voltage cable line can be:

[0076] M DT =(M 3D ,M dynamic );

[0077] The response change results can be:

[0078]

[0079] The operation and maintenance decision plan (i.e., operation strategy) can be:

[0080] G Decision =f decision (R response ,R Diagnosis );

[0081] The calculation formula for adjusting the digital twin model can be:

[0082]

[0083] Among them, M DT It can be used to characterize the digital twin model of high-voltage cable lines. 3D Can be used to characterize the three-dimensional structure model of the cable, M dynamic It can be used to characterize the dynamic model of cable operation status, R response Can be used to characterize the response change result parameters, Can be used to characterize the current state vector of the cable, G Decision It can be used to characterize the operation and maintenance decision-making plan, f decision (·) can be used to characterize the decision-making function, R Diagnosis It can be used to characterize the abnormal status of the cable and diagnose the cause. It can be used to characterize the digital twin model after feedback adjustment, and β can be used to characterize the feedback adjustment factor. Can be used to characterize feedback data vectors.

[0084] In this embodiment, by constructing a digital twin model and combining it with real-time operation data, dynamic monitoring of high-voltage cable lines is achieved, the operating status and potential risks of the cable lines are reflected in a timely manner, and scientific and reasonable operation and maintenance decision-making plans are generated based on the response change results and abnormal status diagnosis simulated by the digital twin model, thereby improving the efficiency of cable maintenance, reducing the occurrence of failures and extending the service life of equipment.

[0085] Optionally, the digital twin model can be adjusted through feedback data input by the user to achieve continuous optimization, so that the digital twin model can adapt to changes in the actual operating environment, provide a decision-making basis for the intelligent operation and maintenance of high-voltage cables, improve the overall operation and maintenance management level, and reduce the need for manual intervention. Among them, the above feedback data can be used to characterize the evaluation results of the response results.

[0086] In this embodiment, a digital twin model of the high-voltage cable line is constructed based on the three-dimensional structure model of the cable and the dynamic model of the operating status. The digital twin model is used to simulate the response changes of the cable line under different operating strategies. Combined with the abnormal diagnosis results, targeted operation and maintenance decision plans (i.e., target operation strategies) are generated, and the digital twin model is continuously optimized through feedback data to improve the effectiveness of decision-making.

[0087] As an optional implementation, based on the operating data, a three-dimensional cable structure of the cable line is constructed, including: determining the acoustic signal characteristics of the acoustic pulse sensor signal in the operating data; extracting the acoustic signal characteristics to obtain the propagation delay of the acoustic pulse sensor signal; based on the propagation delay and the acoustic propagation path of the acoustic pulse sensor signal, determining the path propagation effect data of the acoustic pulse sensor signal; based on the path propagation effect data, constructing the three-dimensional cable structure.

[0088] In this embodiment, the three-dimensional structure of the cable can be constructed by the following steps: the acoustic wave signal characteristics of the acoustic wave pulse sensor signal in the operating data can be determined; the acoustic wave signal characteristics are extracted to obtain the propagation delay of the acoustic wave pulse sensor signal; based on the propagation delay and the acoustic wave propagation path of the acoustic wave pulse sensor signal, the path propagation effect data of the acoustic wave pulse sensor signal is determined; based on the path propagation effect data, the three-dimensional structure of the cable is constructed.

[0089] Optionally, through time domain analysis, the acoustic signal characteristics of the acoustic pulse sensor signal can be extracted, the propagation delay of the acoustic pulse sensor signal can be calculated, and the arrival time of the acoustic pulse sensor signal from different paths can be measured by phase difference to obtain the acoustic propagation path of the acoustic pulse sensor signal. Based on the propagation delay and the acoustic propagation path, the acoustic multipath propagation effect data (that is, path propagation effect data) of the acoustic pulse sensor signal is extracted. Based on the path propagation effect data, the three-dimensional structure of the cable can be constructed. The method for constructing the three-dimensional structure of the cable based on the path propagation effect data is further described below.

[0090] As an optional implementation, a three-dimensional cable structure is constructed based on path propagation effect data, including: dividing the cable line according to the geometric shape and material properties of the cable line to obtain at least one divided area; separating the path propagation effect data according to the at least one divided area to obtain regional data corresponding to the at least one divided area; converting the path propagation effect data into an acoustic wave propagation trajectory of an acoustic wave pulse sensing signal; and constructing a three-dimensional cable structure based on the acoustic wave propagation trajectory and the regional data.

[0091] In this embodiment, based on the sound wave multipath propagation effect data, a sound wave propagation trajectory can be formed, and the high-voltage cable line can be divided into several regional units according to the geometric shape and material properties of the cable line by a uniform grid division method to obtain at least one divided area. According to at least one divided area, the sound wave multipath propagation effect data can be divided by regional units to obtain regional data (that is, regional unit data) corresponding to at least one divided area. Based on the sound wave propagation trajectory and regional unit data, a cable three-dimensional structure can be constructed, and a cable operation state dynamic model can be established based on the cable operation state data. Further, based on the cable three-dimensional structure and dynamic model, a digital twin model can be constructed.

[0092] Optionally, by extracting the characteristics of the acoustic pulse sensor signal through time domain analysis, calculating the propagation delay and measuring the arrival time of different paths, the multi-path propagation effect data of the acoustic wave can be obtained, providing basic data for constructing the three-dimensional structure of the cable, and forming the acoustic wave propagation trajectory based on the acoustic wave multi-path propagation effect data. In combination with the geometric shape and material properties of the cable line, the cable line is divided into multiple area units using a uniform grid division method, thereby obtaining multiple divided areas, which can further describe the three-dimensional structure of the cable more finely.

[0093] In this embodiment, the sound wave multipath propagation effect data is combined with the regional unit data to construct a three-dimensional structural model of the cable, and a cable operation status dynamic model is established based on the cable operation status data. The cable three-dimensional structural model is constructed based on the sound wave propagation trajectory and the regional unit data, so that a more intuitive understanding of the spatial distribution and structural characteristics of the cable can be obtained. The cable operation status dynamic model is established in combination with the cable operation status data, which can reflect the changes in the cable operation status in real time, provide a basis for fault diagnosis and maintenance decisions, and improve the safety of the cable line.

[0094] Optionally, the calculation formula of the cable three-dimensional structure model can be:

[0095] Γ(t)=(x(t),y(t),z(t));

[0096] V ijk =(x i ,y j ,z k );

[0097] x i ,y j ,z k =x0+i·Δx,y0+j·Δy,z0+k·Δz;

[0098] ρ ijk =ρ(x i ,y j ,zk );

[0099] E ijk =E(x i ,y j ,z k );

[0100] ν ijk =ν(x i ,y j ,z k );

[0101] M 3D ={(V ijk ,ρ ijk ,E ijk ,ν ijk )|i=1,M;j=1,N;k=1,P};

[0102] Among them, Γ(t) can be the propagation trajectory of the sound wave, x(t), y(t), z(t) can be the horizontal, vertical and vertical coordinates of the sound wave at time t, respectively, V ijk can be the three-dimensional coordinates of the regional unit of the i-th row, j-th column and k-th layer of the high-voltage cable line, x i ,y j 、z k can be the horizontal, vertical and vertical coordinates of the i-th row regional unit, the j-th column regional unit and the k-th layer regional unit respectively, x0, y0 and z0 can be the horizontal, vertical and vertical coordinates of the starting position of the cable respectively, Δx, Δy and Δz can be the horizontal, vertical and vertical dimensions of the regional unit in three-dimensional space respectively, ρ ijk 、E ijk , ν ijk The material density, elastic modulus and Poisson's ratio of the i-th row, j-th column and k-th layer of the high-voltage cable line can be assigned respectively. ρ(·), E(·) and ν(·) can be the material density property function, elastic modulus property function and Poisson's ratio property function under the horizontal and vertical coordinates of the three-dimensional space respectively. 3D It can be a three-dimensional cable structure model, and M, N, and P can be the number of regional units in the horizontal, longitudinal, and vertical directions, respectively.

[0103] Optionally, this embodiment accurately constructs a three-dimensional structural model of the cable by calculating the three-dimensional coordinates of the acoustic wave propagation trajectory and the regional unit, providing a detailed description of the internal structure of the cable, which helps to identify potential defects and abnormalities of the cable. The three-dimensional structural model of the cable integrates physical properties such as material density, elastic modulus and Poisson's ratio, which can more comprehensively reflect the characteristics of the cable material, thereby improving the accuracy of the cable performance analysis. And by dividing the cable line into multiple regional units and performing detailed size division in three-dimensional space, the spatial resolution of the three-dimensional structural model of the cable is enhanced. The three-dimensional structural model of the cable simulates the response changes of the cable under different operating conditions, controls the changes in the geometric properties of the cable, and provides support for fault diagnosis and maintenance decisions.

[0104] In this embodiment, the acoustic wave pulse sensor signal is analyzed to obtain acoustic wave multipath propagation effect data, which includes the acoustic wave propagation trajectory. Furthermore, the acoustic wave multipath propagation effect data is divided into regional units to obtain regional unit data, and a three-dimensional structure model of the cable is constructed based on the acoustic wave propagation trajectory and the regional unit data, and a dynamic model of the cable operation status is established based on the cable operation status data.

[0105] As an optional implementation, collecting the operation data of the cable line includes: acquiring the operation data collected by the distributed optical fiber sensing system and / or the discharge detection equipment.

[0106] In this embodiment, the operating data may be collected by a distributed optical fiber sensing system and / or a discharge detection device.

[0107] Optionally, the partial discharge signal of the cable body, the partial discharge signal of the cable joint and the partial discharge signal of the cable terminal can be monitored by the partial discharge detection equipment. The above-mentioned grounding system monitoring data may include the real-time resistance and temperature data of the cable grounding node, and the real-time resistance and temperature data of the grounding node are collected by the grounding resistance online monitoring system. Optionally, by deploying a distributed optical fiber sensing system, the temperature and stress state of the cable can be monitored in real time, so as to obtain the dynamic information of the cable operation in time, and the partial discharge detection equipment can be used to monitor the partial discharge signals of the cable body, joints and terminals, so as to enhance the early identification and accurate diagnosis capabilities of cable faults.

[0108] As an optional implementation, step S104, in response to the operating state being an abnormal operating state, determines multiple operating strategies for the cable line, including: in response to the operating state being an abnormal operating state, using a state recognition model to identify abnormal operating data in the abnormal operating state to obtain the abnormal cause of the operating state, wherein the state recognition model is trained based on historical abnormal operating data of the cable line; and determines multiple operating strategies corresponding to the abnormal causes.

[0109] In this embodiment, a state recognition model can also be constructed based on a deep learning algorithm. The state recognition model can be a cable abnormal state recognition model, which can be trained based on historical abnormal operation data of the cable line and can be used to identify the cause of the abnormal operation state of the cable line. Further, the cable abnormal state data can be identified by the cable abnormal state recognition model to obtain the abnormal cause of the abnormal operation state (that is, the cause of the cable abnormal state diagnosis). Based on the abnormal cause, multiple operation strategies corresponding to the abnormal cause can be determined, and the operation strategy can be used to solve the abnormality of the cable line.

[0110] Optionally, constructing an initial cable abnormal state recognition model based on a deep learning neural network may include the following steps: obtaining historical cable abnormal state data (that is, the above-mentioned historical abnormal operation data) from a historical database, and dividing the historical cable abnormal state data into a training set and a test set; iteratively training the initial cable abnormal state recognition model through the training set, configuring the loss function and hyperparameters until the iteration stop condition is reached, and obtaining the trained initial cable abnormal state recognition model, and the iteration stop condition may include: the loss function converges and the number of iterations reaches a preset value; using the test set to test the trained initial cable abnormal state recognition model, and evaluating the initial cable abnormal state recognition model through the mean average precision (mAP) value, when the initial cable abnormal state recognition model evaluation meets the requirements, the cable abnormal state recognition model (that is, the above-mentioned state recognition model) is obtained, otherwise the initial cable abnormal state recognition model is iteratively trained again after adjusting the hyperparameters. It should be noted that the above-mentioned method of obtaining a state recognition model based on historical abnormal operation data training is only an example, and no specific limitation is made here.

[0111] Optionally, the above hyperparameters may include learning rate, batch sample size, optimizer, number of deep learning network layers, and number of neurons.

[0112] For example, the initial cable abnormal state recognition model can be constructed by the following steps: select a deep learning framework (such as TensorFlow) and construct a convolutional neural network (CNN) model including an input layer, multiple convolutional layers, a pooling layer, a fully connected layer and an output layer. From the historical database storing historical abnormal operation data, extract various cable abnormal state data that occurred within 10 years, such as temperature anomaly, partial discharge, grounding anomaly, etc., totaling 1000 data samples. Randomly divide the data into 800 training sets and 200 test sets; iteratively train the initial CNN model on the training set, using the cross entropy loss function, the optimizer is the adaptive moment estimation (Adam), the initial learning rate is set to 0.001, the batch sample size is 32, the number of network layers is 5, and the number of neurons in each layer is 64, 128, 256, 128, and 64 respectively; when the loss function does not decrease significantly in 5 consecutive training cycles, or reaches 100 training cycles, stop training, and obtain the trained initial cable abnormal state recognition model. The trained initial model is evaluated using the test set, and the mAP index of the model on the test set is calculated; if the mAP reaches above 0.75, the model can be used as a cable abnormal state recognition model. Otherwise, the hyperparameters are adjusted, such as reducing the learning rate to 0.0005, increasing the batch sample size to 64, and re-training the model. It should be noted that the above numbers are only for example and are not specifically limited here.

[0113] In this embodiment, the abnormal state of the cable is identified through iterative training of the deep learning algorithm, the operating state of the cable is monitored in real time, potential anomalies are identified in time, and the risk of power outages caused by cable failures is reduced. By adjusting the hyperparameters, it adapts to different cable operating environments and states, enhances the flexibility of the model, and adjusts the learning rate, batch sample size, optimizer, number of network layers and number of neurons as hyperparameters to optimize the performance of the model according to the different characteristics of cable abnormal state data.

[0114] In this embodiment, based on the response change results and the causes of the cable abnormal status diagnosis, a corresponding operation and maintenance decision plan can be generated, feedback data generated when the operation and maintenance decision plan is executed can be collected, and the digital twin model can be adjusted based on the feedback data.

[0115] Optionally, based on the diagnosis cause of the abnormal state of the cable (i.e., the cause of the abnormality), multiple operation strategies can be determined, and the digital twin model can be adjusted according to the operation strategies to obtain response change results under different operation strategies. Furthermore, based on different response change results, the target operation strategy can be determined from multiple operation strategies.

[0116] In this embodiment, a three-dimensional structural model of the cable and a dynamic model of the cable operation status are constructed through three-dimensional acoustic wave scanning, multipath propagation effect analysis, deep learning and digital twin models. The deep learning algorithm is used to identify abnormal cable conditions and diagnose the causes. The operation and maintenance decision plan is generated based on the digital twin simulation of the cable response changes, thereby realizing the three-dimensional digital operation and decision-making of the high-voltage cable line, effectively improving the monitoring and diagnosis accuracy of the cable line and the targeted operation and maintenance decision-making.

[0117] In the related technologies, the monitoring and diagnosis of high-voltage cable lines usually only rely on acoustic three-dimensional scanning technology and multi-path propagation effect analysis methods. However, the accuracy of acoustic three-dimensional scanning and multi-path propagation effect analysis is limited by the resolution of the equipment and the complexity of the algorithm, resulting in inaccurate capture of the details of the internal structure of the cable, thus resulting in low efficiency in maintaining the operating status of the cable line. Technical problems.

[0118] In this embodiment, in order to solve the above problems, a cable three-dimensional structural model and a cable operation status dynamic model are constructed through three-dimensional acoustic wave scanning, multi-path propagation effect analysis, deep learning and digital twin models, and the abnormal state of the cable is identified and the cause is diagnosed by using a deep learning algorithm. Based on the digital twin simulation cable response change, an operation and maintenance decision plan is generated, thereby realizing the internal structure analysis and monitoring of the high-voltage cable line, and effectively improving the monitoring accuracy of the cable line. The characteristics of the acoustic wave pulse sensor signal are extracted through time domain analysis, the propagation delay is calculated, and the arrival time of different paths is measured to obtain the acoustic wave multi-path propagation effect data. Based on the acoustic wave propagation trajectory and regional unit data, a three-dimensional structural model of the cable is constructed, and a structural model of the cable that changes with the operation state is provided. Based on the cable three-dimensional structural model and the operation state dynamic model, a digital twin model of the high-voltage cable line is constructed to simulate the response changes of the cable in different states, and combined with the abnormal diagnosis results, a targeted operation and maintenance decision plan is generated, and the digital twin model is continuously optimized through feedback data to improve the effectiveness of the decision.

[0119] In the embodiment of the present application, a three-dimensional digital intelligent operation and decision-making system for high-voltage cable lines is also provided. Figure 2 is a schematic diagram of an operation and decision-making system according to an embodiment of the present application, such as Figure 2 As shown, the operation and decision-making system 200 may include the following parts:

[0120] The data acquisition module 201 can be used to collect original multimodal data of the high-voltage cable line, pre-process the original multimodal data, and obtain high-voltage cable data, wherein the high-voltage cable data (ie, operation data) may include acoustic pulse sensor signals and cable operation status data.

[0121] The three-dimensional modeling module 202 is used to analyze the acoustic wave pulse sensor signal to obtain the acoustic wave multipath propagation effect data, the acoustic wave multipath propagation effect data includes the acoustic wave propagation trajectory, divide the acoustic wave multipath propagation effect data into regional units to obtain regional unit data, build a cable three-dimensional structure model (that is, the cable three-dimensional structure) based on the acoustic wave propagation trajectory and the regional unit data, and establish a cable operation status dynamic model (that is, the dynamic model) based on the cable operation status data.

[0122] The abnormal diagnosis module 203 is used to monitor the cable operation status dynamic model in real time, obtain the cable abnormal status data (that is, the operation data under the abnormal operation state), build a cable abnormal status recognition model (that is, the recognition model) based on the deep learning algorithm, identify the cable abnormal status data through the cable abnormal status recognition model, and obtain the cause of the cable abnormal status diagnosis.

[0123] The operation and maintenance decision module 204 is used to build a digital twin model of the high-voltage cable line based on the cable three-dimensional structure model and the cable operation status model, simulate the response change results of the cable under different cable operation states through the digital twin model, generate corresponding operation and maintenance decision plans (that is, target operation strategies) based on the response change results and the causes of the cable abnormal state diagnosis, collect feedback data generated during the execution of different operation and maintenance decision plans, and adjust the digital twin model based on the feedback data.

[0124] Optionally, multimodal raw data of the high-voltage cable line, including acoustic pulse sensor signals and cable operating status data, is collected through the data acquisition module, and the acoustic wave signals are analyzed based on the three-dimensional modeling module to extract the acoustic wave multipath propagation effect data. Based on this, a three-dimensional structural model and an operating status dynamic model of the cable are constructed to provide basic data support for abnormal diagnosis and decision-making.

[0125] Optionally, the abnormality diagnosis module builds a cable abnormal state recognition model based on a deep learning algorithm, and monitors the cable operation status in real time, accurately identifies the cable abnormal state and diagnoses its root cause based on the cable abnormal state recognition model.

[0126] Optionally, the operation and maintenance decision module builds a virtual digital twin model based on the cable 3D structure model and the dynamic model of the operating status to simulate the response changes of the cable under different operating conditions. Combined with the abnormal diagnosis results, the module can generate targeted operation and maintenance decision plans, and continuously optimize the digital twin model through feedback data to improve the effectiveness of decision-making.

[0127] Optionally, the above system realizes comprehensive monitoring and intelligent diagnosis of the cable operation status, providing a decision-making basis for the operation and maintenance of the cable.

[0128] According to an embodiment of the present application, a cable line operation device is also provided. It should be noted that the cable line operation device of this embodiment can be used to execute the cable line operation method of embodiment 1 of the present application.

[0129] Figure 3 Schematic diagram of a cable line operation device according to an embodiment of the present application. Figure 3 As shown, the cable line operation device 30 may include: a first determination unit 302 , a second determination unit 304 , a simulation unit 306 , a third determination unit 308 and an operation unit 310 .

[0130] The first determining unit 302 is used to determine the operating status of the cable line.

[0131] The second determining unit 304 is used to determine a plurality of operating strategies of the cable line in response to the operating state being an abnormal operating state, wherein the operating strategy is used to represent a rule for operating the cable line.

[0132] The simulation unit 306 is used to use the digital twin model of the cable line to simulate the response results of the cable line under multiple operation strategies to obtain multiple response results.

[0133] The third determining unit 308 is configured to determine a target operation strategy from among multiple operation strategies based on the multiple response results.

[0134] The operation unit 310 is used to operate the cable line according to the target operation strategy.

[0135] The operation device of the cable line of this embodiment determines the operation status of the cable line through a first determination unit; determines multiple operation strategies of the cable line in response to the operation status being an abnormal operation status through a second determination unit, wherein the operation strategy is used to represent the rules for operating the cable line; simulates the response results of the cable line under multiple operation strategies respectively by using a digital twin model of the cable line through a simulation unit, and obtains multiple response results; determines a target operation strategy from multiple operation strategies based on multiple response results through a third determination unit; and operates the cable line according to the target operation strategy through an operation unit, thereby achieving the technical effect of improving the maintenance efficiency of the operation status of the cable line and solving the technical problem of low efficiency in maintaining the operation status of the cable line.

[0136] The embodiment of the present application may provide a computer terminal, which may be any computer terminal device in a computer terminal group. Optionally, in this embodiment, the computer terminal may also be replaced by a terminal device such as a mobile terminal.

[0137] Optionally, in this embodiment, the computer terminal may be located in at least one network device among a plurality of network devices of the computer network.

[0138] In this embodiment, the above-mentioned computer terminal can execute the program code of the following steps in the operation method of the cable line: determine the operating status of the cable line; in response to the operating status being an abnormal operating status, determine multiple operating strategies for the cable line, wherein the operating strategy is used to represent the rules for operating the cable line; use the digital twin model of the cable line to simulate the response results of the cable line under multiple operating strategies respectively, and obtain multiple response results; based on the multiple response results, determine the target operating strategy from the multiple operating strategies; operate the cable line according to the target operating strategy.

[0139] Optionally, Figure 4 is a structural block diagram of a computer terminal according to an embodiment of the present application, such as Figure 4 As shown, the computer terminal 408 may include: one or more (only one is shown in the figure) processors 402 , a memory 404 and a transmission device 406 .

[0140] Among them, the memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the operation method and device of the cable line in the embodiment of the present application. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, that is, realizing the operation method of the above-mentioned cable line. The memory may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory may further include a memory remotely arranged relative to the processor, and these remote memories can be connected to the computer terminal 408 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0141] The processor can call the information and application programs stored in the memory through the transmission device to perform the following steps: determine the operating status of the cable line; in response to the operating status being an abnormal operating status, determine multiple operating strategies for the cable line, wherein the operating strategy is used to represent the rules for operating the cable line; use the digital twin model of the cable line to simulate the response results of the cable line under multiple operating strategies respectively, and obtain multiple response results; based on the multiple response results, determine the target operating strategy from the multiple operating strategies; and operate the cable line according to the target operating strategy.

[0142] It can be understood by those skilled in the art that Figure 4The structure shown is for illustration only, and the computer terminal 408 may also be a smart phone (such as an Android phone, an iOS phone, etc.), a tablet computer, a PDA, a mobile Internet device (MID for short), a PAD, or other terminal devices. Figure 4 The structure of the computer terminal 408 is not limited. For example, the computer terminal 408 may also include Figure 4 More or fewer components (such as network interfaces, display devices, etc.) shown in, or having Figure 4 Different configurations are shown.

[0143] A person of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing the hardware related to the terminal device through a program, and the program can be stored in a computer-readable storage medium, and the storage medium may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, etc.

[0144] According to an embodiment of the present application, a computer-readable storage medium is also provided, which includes a stored program, wherein the program executes the operating method of the cable line in Example 1.

[0145] Optionally, in this embodiment, the computer-readable storage medium may be located in any one of the computer terminals in a computer terminal group in a computer network, or in any one of the mobile terminals in a mobile terminal group.

[0146] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: determining the operating status of the cable line; in response to the operating status being an abnormal operating status, determining multiple operating strategies for the cable line, wherein the operating strategies are used to represent the rules for operating the cable line; using a digital twin model of the cable line, simulating the response results of the cable line under multiple operating strategies respectively, and obtaining multiple response results; based on the multiple response results, determining a target operating strategy from the multiple operating strategies; and operating the cable line according to the target operating strategy.

[0147] Optionally, the computer-readable storage medium may also execute program codes of the following steps: collecting operation data of the cable line; and determining the operation status based on the operation data.

[0148] Optionally, the computer-readable storage medium may also execute program codes of the following steps: constructing a dynamic model of the cable line based on the operating data, wherein the dynamic model is used to characterize the changes in the operating state of the cable line under multiple operating data; monitoring the dynamic model in real time to obtain monitoring results; and determining the operating state based on the monitoring results.

[0149] Optionally, the computer-readable storage medium may also execute program code of the following steps: constructing a dynamic model based on cable operation status data in the operation data, wherein the cable operation status data is at least used to characterize electrical characteristics of the cable line.

[0150] Optionally, the computer-readable storage medium can also execute program codes of the following steps: based on the operating data, construct a three-dimensional cable structure of the cable line, wherein the three-dimensional cable structure is at least used to characterize the geometric shape of the cable line; based on the three-dimensional cable structure and the dynamic model, construct a digital twin model.

[0151] Optionally, the computer-readable storage medium may also execute program codes of the following steps: determining acoustic signal characteristics of the acoustic pulse sensor signal in the operating data; extracting the acoustic signal characteristics to obtain the propagation delay of the acoustic pulse sensor signal; determining the path propagation effect data of the acoustic pulse sensor signal based on the propagation delay and the acoustic propagation path of the acoustic pulse sensor signal; and constructing a three-dimensional structure of the cable based on the path propagation effect data.

[0152] Optionally, the computer-readable storage medium can also execute program codes for the following steps: dividing the cable line according to the geometric shape and material properties of the cable line to obtain at least one divided area; separating the path propagation effect data according to at least one divided area to obtain regional data corresponding to at least one divided area; converting the path propagation effect data into an acoustic wave propagation trajectory of an acoustic wave pulse sensing signal; and constructing a three-dimensional structure of the cable based on the acoustic wave propagation trajectory and the regional data.

[0153] Optionally, the computer-readable storage medium may also execute program codes for the following steps: acquiring operation data collected by the distributed optical fiber sensing system and / or the discharge detection device.

[0154] Optionally, the computer-readable storage medium may also execute program codes of the following steps: in response to an operating state being an abnormal operating state, using a state recognition model to identify abnormal operating data in the abnormal operating state to obtain an abnormal cause of the operating state, wherein the state recognition model is trained based on historical abnormal operating data of the cable line; and determining multiple operating strategies corresponding to the abnormal causes.

[0155] In this embodiment, the operating status of the cable line is determined. If the operating status of the cable line is an abnormal operating status, multiple operating strategies (i.e., maintenance strategies) for maintaining the high-voltage cable line can be determined. By using the digital twin model, the most suitable target operating strategy among the operating strategies can be determined, and the cable line is maintained according to the target operating strategy, thereby achieving the technical effect of improving the maintenance efficiency of the operating status of the cable line and solving the technical problem of low efficiency in maintaining the operating status of the cable line.

[0156] According to an embodiment of the present application, a processor is also provided, which is used to run a program, wherein when the program is run by the processor, the cable line operation method in Example 1 is executed.

[0157] Optionally, in this embodiment, the computer terminal may be located in at least one network device among a plurality of network devices of the computer network.

[0158] In this embodiment, the above-mentioned computer terminal can execute the program code of the following steps in the operation method of the cable line: determine the operating status of the cable line; in response to the operating status being an abnormal operating status, determine multiple operating strategies for the cable line, wherein the operating strategy is used to represent the rules for operating the cable line; use the digital twin model of the cable line to simulate the response results of the cable line under multiple operating strategies respectively, and obtain multiple response results; based on the multiple response results, determine the target operating strategy from the multiple operating strategies; operate the cable line according to the target operating strategy.

[0159] Wherein, the memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the operation method and device of the cable circuit in the embodiment of the present application, and the processor executes various functional applications and data processing by running the software programs and modules stored in the memory, that is, realizing the operation method of the above-mentioned cable circuit. The memory may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include a memory remotely arranged relative to the processor, and these remote memories may be connected to the computer terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0160] The processor can call the information and application programs stored in the memory through the transmission device to perform the following steps: determine the operating status of the cable line; in response to the operating status being an abnormal operating status, determine multiple operating strategies for the cable line, wherein the operating strategy is used to represent the rules for operating the cable line; use the digital twin model of the cable line to simulate the response results of the cable line under multiple operating strategies respectively, and obtain multiple response results; based on the multiple response results, determine the target operating strategy from the multiple operating strategies; and operate the cable line according to the target operating strategy.

[0161] Optionally, the processor may also execute program codes of the following steps: collecting operation data of the cable line; and determining the operation status based on the operation data.

[0162] Optionally, the processor may also execute the program code of the following steps: constructing a dynamic model of the cable line based on the operating data, wherein the dynamic model is used to characterize the changes in the operating state of the cable line under multiple operating data; monitoring the dynamic model in real time to obtain monitoring results; and determining the operating state based on the monitoring results.

[0163] Optionally, the processor may also execute program code of the following steps: constructing a dynamic model based on cable operation status data in the operation data, wherein the cable operation status data is at least used to characterize electrical characteristics of the cable line.

[0164] Optionally, the processor may also execute the program code of the following steps: constructing a three-dimensional cable structure of the cable line based on the operating data, wherein the three-dimensional cable structure is at least used to characterize the geometric shape of the cable line; and constructing a digital twin model based on the three-dimensional cable structure and the dynamic model.

[0165] Optionally, the processor may also execute the program code of the following steps: determining the acoustic signal characteristics of the acoustic pulse sensor signal in the operating data; extracting the acoustic signal characteristics to obtain the propagation delay of the acoustic pulse sensor signal; determining the path propagation effect data of the acoustic pulse sensor signal based on the propagation delay and the acoustic propagation path of the acoustic pulse sensor signal; and constructing a three-dimensional structure of the cable based on the path propagation effect data.

[0166] Optionally, the processor may also execute program codes of the following steps: dividing the cable line according to the geometric shape and material properties of the cable line to obtain at least one divided area; separating the path propagation effect data according to at least one divided area to obtain regional data corresponding to at least one divided area; converting the path propagation effect data into an acoustic wave propagation trajectory of an acoustic wave pulse sensing signal; and constructing a three-dimensional structure of the cable based on the acoustic wave propagation trajectory and the regional data.

[0167] Optionally, the processor may also execute program codes of the following steps: acquiring operation data collected by the distributed optical fiber sensing system and / or the discharge detection device.

[0168] Optionally, the processor may also execute the program code of the following steps: in response to the operating state being an abnormal operating state, using a state recognition model to identify abnormal operating data in the abnormal operating state to obtain the abnormal cause of the operating state, wherein the state recognition model is trained based on historical abnormal operating data of the cable line; and determining multiple operating strategies corresponding to the abnormal causes.

[0169] By using the embodiment of the present application, the operating status of the cable line is determined. If the operating status of the cable line is an abnormal operating status, multiple operating strategies (i.e., maintenance strategies) for maintaining the high-voltage cable line can be determined. By using the digital twin model, the most suitable target operating strategy among the operating strategies can be determined, and the cable line can be maintained according to the target operating strategy, thereby achieving the technical effect of improving the maintenance efficiency of the operating status of the cable line and solving the technical problem of low efficiency in maintaining the operating status of the cable line.

[0170] According to an embodiment of the present application, a computer program product is also provided, which includes computer instructions, wherein the computer instructions implement the operation method of the cable line in Example 1 when executed by a processor.

[0171] An embodiment of the present application may provide an electronic device, which may include a memory and a processor.

[0172] Figure 5 It is a block diagram of an electronic device according to a method of operating a cable line according to an embodiment of the present application. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present application described and / or required herein.

[0173] like Figure 5As shown, the device 500 includes a computing unit 501, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 502 or a computer program loaded from a storage unit 508 to a random access memory (RAM) 503. In the RAM 503, various programs and data required for the operation of the device 500 can also be stored. The computing unit 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0174] A number of components in the device 500 are connected to the I / O interface 505, including: an input unit 506, such as a keyboard, a mouse, etc.; an output unit 507, such as various types of displays, speakers, etc.; a storage unit 508, such as a disk, an optical disk, etc.; and a communication unit 509, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 509 allows the device 500 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0175] The computing unit 501 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 501 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The computing unit 501 performs the various methods and processes described above, such as a verification method for data. For example, in some embodiments, the verification method for data may be implemented as a computer software program, which is tangibly included in a machine-readable medium, such as a storage unit 508. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 500 via the ROM 502 and / or the communication unit 509. When the computer program is loaded into the RAM 503 and executed by the computing unit 501, one or more steps of the verification method for data described above may be executed. Alternatively, in other embodiments, the computing unit 501 may be configured to execute the data verification method in any other appropriate manner (for example, by means of firmware).

[0176] According to an embodiment of the present application, a method for operating a cable line is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0177] Various embodiments of the systems and techniques described above herein may be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on a chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include: being implemented in one or more computer programs that may be executed and / or interpreted on a programmable system including at least one programmable processor that may be a dedicated or general purpose programmable processor that may receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0178] The program code for implementing the method of the present application can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code can be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0179] In the context of the present application, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0180] To provide interaction with a user, the systems and techniques described herein may be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or an LCD (liquid crystal display, monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a path ball) through which the user can provide input to the computer. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0181] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a Local Area Network (LAN), a Wide Area Network (WAN), and the Internet.

[0182] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0183] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0184] In the above embodiments of the present application, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0185] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0186] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed over multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0187] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0188] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or all or part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of each embodiment method of the present application. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk, etc. Various media that can store program codes.

[0189] The above are only preferred implementations of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for operating a cable line, characterized in that: include: Determine the operating status of the cable line; In response to the operating state being an abnormal operating state, determining a plurality of operating strategies of the cable line, wherein the operating strategies are used to represent rules for operating the cable line; Using the digital twin model of the cable line, simulating the response results of the cable line under the multiple operation strategies respectively, and obtaining multiple response results; Based on the plurality of response results, determining a target operation strategy from the plurality of operation strategies; The cable line is operated according to the target operation strategy.

2. The method according to claim 1, characterized in that Determining the operating status of the cable line includes: Collecting operation data of the cable line; Based on the operating data, the operating status is determined.

3. The method according to claim 2, characterized in that The determining the operating state based on the operating data includes: Based on the operation data, construct a dynamic model of the cable line, wherein the dynamic model is used to characterize the change of the operation state of the cable line under the plurality of operation data; Performing real-time monitoring on the dynamic model to obtain monitoring results; Based on the monitoring result, the operating status is determined.

4. The method according to claim 3, characterized in that The step of constructing a dynamic model of the cable line based on the operation data comprises: The dynamic model is constructed based on the cable operation status data in the operation data, wherein the cable operation status data is at least used to characterize the electrical characteristics of the cable line.

5. The method according to claim 3, characterized in that: The method further comprises: Based on the operation data, construct a three-dimensional cable structure of the cable line, wherein the three-dimensional cable structure is at least used to characterize a geometric shape of the cable line; The digital twin model is constructed based on the three-dimensional structure of the cable and the dynamic model.

6. The method according to claim 5, characterized in that The step of constructing a three-dimensional cable structure of the cable line based on the operation data comprises: determining an acoustic signal characteristic of an acoustic pulse sensor signal in the operating data; Extracting the acoustic wave signal characteristics to obtain the propagation delay of the acoustic wave pulse sensor signal; Determining path propagation effect data of the acoustic wave pulse sensor signal based on the propagation time delay and the acoustic wave propagation path of the acoustic wave pulse sensor signal; Based on the path propagation effect data, the three-dimensional structure of the cable is constructed.

7. The method according to claim 6, characterized in that The constructing of the three-dimensional structure of the cable based on the path propagation effect data comprises: Dividing the cable line according to the geometric shape and the material properties of the cable line to obtain at least one divided area; Separating the path propagation effect data according to at least one of the divided areas to obtain area data corresponding to at least one of the divided areas; Converting the path propagation effect data into the acoustic wave propagation trajectory of the acoustic wave pulse sensor signal; Based on the acoustic wave propagation trajectory and the area data, the three-dimensional structure of the cable is constructed.

8. The method according to claim 2, characterized in that: The collecting of the operation data of the cable line includes: The operating data collected by the distributed optical fiber sensing system and / or the discharge detection device is obtained.

9. The method according to claim 1, characterized in that: In response to the operating state being an abnormal operating state, determining a plurality of operating strategies for the cable line comprises: In response to the operating state being the abnormal operating state, using a state recognition model to recognize abnormal operating data in the abnormal operating state to obtain an abnormal cause of the operating state, wherein the state recognition model is trained based on historical abnormal operating data of the cable line; A plurality of the operating strategies corresponding to the abnormal causes are determined.

10. A cable line operation device, characterized in that: include: A first determining unit, used to determine the operating status of the cable line; a second determining unit, configured to determine a plurality of operating strategies of the cable line in response to the operating state being an abnormal operating state, wherein the operating strategy is used to represent a rule for operating the cable line; A simulation unit, used to simulate the response results of the cable line under the multiple operation strategies respectively by using the digital twin model of the cable line, and obtain multiple response results; A third determining unit, configured to determine a target operation strategy from the plurality of operation strategies based on the plurality of response results; An operation unit is used to operate the cable line according to the target operation strategy.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the method according to any one of claims 1 to 9.

12. A processor, characterized in that: The processor is used to run a program, wherein the program executes the method according to any one of claims 1 to 9 when being run by the processor.

13. A computer program product, characterized in that The method comprises computer instructions, which, when executed by a processor, implement the method according to any one of claims 1 to 9.

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