Digital twin management and control method and apparatus for urban cable, device and medium

Abstract

Provided in the present invention is a digital twin management and control method for an urban cable, the method comprising: constructing a digital twin model for an urban cable; acquiring monitoring images of monitoring data, recognizing in each monitoring image an object type and a relative distance to the cable, and generating object impact data; on the basis of temperature data, humidity data and an oxygen content, determining oxidation impact data; when vibration data is greater than a preset threshold, calling corresponding monitoring data on the basis of the digital twin model, so as to determine a vibration source, and, on the basis of the vibration source and corresponding current operating data, generating vibration impact data; on the basis of a cable demand power, the object impact data, the oxidation impact data and the vibration impact data, determining a cable power error range; generating a cable operating state; and, when the cable operating state indicates an operation anomaly, turning off the abnormally operating urban cable, and generating a cable regulation scheme. The present invention can improve the effect of urban cable management and control.

Description

A digital twin management method, device, equipment and medium for urban cables Technical Field

[0001] This invention relates to the field of power system technology, and more specifically, to a digital twin management method, device, equipment, and medium for urban cables. Background Technology

[0002] Urban cables are a vital component of urban infrastructure, used to transmit electricity, communications, and data. Urban cable systems are complex networks composed of various types of cables, connected to buildings, streets, transportation systems, and other parts of the city through underground or overhead installations. Urban cables carry critical information and services necessary for urban life and operation, playing a crucial role in the city's development and functioning.

[0003] Currently, to ensure the integrity and performance of urban cable systems, regular maintenance and inspection are commonly used for management. However, this approach has a significant problem: a lack of real-time capability. Regular maintenance and inspection often fail to detect cable problems in a timely manner, resulting in ineffective urban cable management. Technical issues

[0004] In view of the above-mentioned shortcomings of the prior art, the present invention addresses the problem of how to improve the control and management of urban cables. Technical solutions

[0005] In a first aspect, the present invention provides a digital twin management and control method for urban cables, comprising:

[0006] Based on the obtained cable parameters, environmental data, and operational data of the urban cable, a digital twin model of the urban cable is constructed; wherein, the environmental data includes monitoring data, temperature data, humidity data, oxygen content, and vibration data, and the operational data includes current operational data, cable power demand, and current cable power.

[0007] The monitoring images of the monitoring data are collected at a preset frequency, the object types and relative cable distances in each monitoring image are identified, and object impact data is generated based on the object types and relative cable distances.

[0008] Based on the temperature data, humidity data, and oxygen content, the oxidation impact data of the urban cable is determined;

[0009] When the vibration data exceeds a preset threshold, the corresponding monitoring data is called according to the digital twin model to determine the vibration source, and vibration impact data is generated based on the vibration source and the corresponding current operating data.

[0010] Based on the cable's required power, the object's influence data, the oxidation influence data, and the vibration influence data, the cable power error range is determined; and based on the cable's current power and the cable power error range, the cable's operating status is generated.

[0011] The object impact data, oxidation impact data, vibration source, vibration impact data, and cable operating status are transmitted to the digital twin model for multi-dimensional display.

[0012] When the cable is in an abnormal operating state, the abnormal city cable is shut down, and a cable control scheme is generated based on the digital twin model.

[0013] Optionally, generating object impact data based on the object type and the relative cable distance includes:

[0014] Based on the type of object and the relative cable distance, physical influence factors and electrical influence factors are generated using physical influence formulas and electrical influence formulas, respectively. The physical influence formulas include:

[0015] PF = h(k) * f(d);

[0016] Wherein, PF is the physical influence factor, h(k) is the risk coefficient function determined according to the object type, k is the object type, f(d) is the risk growth function that varies with the relative cable distance, and d is the relative cable distance;

[0017] The electrical influence formula includes:

[0018] Wherein, EF is the electrical influence factor, g(d) is the degree of electrical interference of conductive objects as the relative cable distance changes, Object non-conduction is a non-conductive object, and Objects conduct electricity is a conductive object;

[0019] Based on the physical influence factor and the electrical influence factor, the comprehensive influence formula is used to generate the object's influence data. The comprehensive influence formula includes: IS = w1 × PF + w2 × EF;

[0020] Wherein, IS represents the object influence data, w1 represents the weighting coefficient of the physical influence factor, and w2 represents the weighting coefficient of the electrical influence factor.

[0021] Optionally, determining the oxidation impact data of the urban cable based on the temperature data, the humidity data, and the oxygen content includes:

[0022] Based on the cable parameters, determine the cable type;

[0023] When the urban cable is an unsheathed cable, a first oxidation formula is used to generate the oxidation effect data based on the temperature data, humidity data, and oxygen content. The first oxidation formula includes:

[0024] Wherein, O represents the oxidation effect data, A represents the initial constant, Ea represents the oxidation rate, R represents the ideal gas constant, T represents the temperature data, H represents the humidity data, m represents the humidity-induced oxidation rate, Ox represents the oxygen content, and n represents the oxygen-induced oxidation rate.

[0025] When the urban cable is a sheathed cable, the oxidation effect data is generated using a second oxidation formula, which includes:

[0026] Where P represents the sheath data, and 1>P>0, and q represents the sheath protection efficiency, and q>1.

[0027] Optionally, determining the cable power error range based on the cable's required power, the object's influence data, the oxidation's influence data, and the vibration's influence data includes:

[0028] Based on the cable power requirement, the object influence data, the oxidation influence data, and the vibration influence data, the minimum power value is determined using an error range formula, which includes: Pmin=(Wi*IS+Wo*O+Wf*F)*Pe*K;

[0029] Wherein, Pmin is the minimum power value, Wi is the object influence weight, IS is the object influence data, Wo is the oxidation influence weight, O is the oxidation influence data, Wf is the vibration influence weight, F is the vibration influence data, Pe is the cable demand power, and K is the correction coefficient;

[0030] The cable power error range is generated based on the minimum power value and the cable power requirement.

[0031] Optionally, generating a cable control scheme based on the digital twin model includes:

[0032] Based on the digital twin model, the cable parameters of the abnormal city cable are called to generate the location of the faulty cable;

[0033] Traverse the idle city cables within the preset area of ​​the faulty cable location and extract the idle cable parameters of the idle city cables;

[0034] Based on the parameters of the idle cable and the power demand of the cable, an optimization algorithm is used to generate the cable control scheme.

[0035] Optionally, constructing a digital twin model of the urban cable based on the acquired cable parameters, environmental data, and operational data includes:

[0036] Obtain the city map corresponding to the city cable;

[0037] Based on the cable parameters and the city map, a 3D model of the cable is constructed; based on the environmental data, an environmental model is constructed; based on the operational data, an electrical model is constructed.

[0038] The cable 3D model, the environment model, and the electrical model are input into the digital twin platform to construct the digital twin model.

[0039] Optionally, the step of acquiring monitoring images of the monitoring data at a preset frequency and identifying the type of object and relative cable distance in each monitoring image includes:

[0040] The monitoring data is collected at the preset frequency to form monitoring images, and an object detection algorithm is used to mark all objects in the monitoring images.

[0041] Extract the image features corresponding to the object, classify the object based on the image features using an image classification algorithm, and generate the object category;

[0042] The pixel size is determined based on the cable parameters and the cable dimensions in the monitoring image;

[0043] The relative cable distance is determined based on the pixel size.

[0044] Secondly, the present invention provides a digital twin management and control device for urban cables, comprising:

[0045] A construction module is used to construct a digital twin model of the urban cable based on the acquired cable parameters, environmental data, and operational data; wherein, the environmental data includes monitoring data, temperature data, humidity data, oxygen content, and vibration data, and the operational data includes current operational data, cable power demand, and current cable power.

[0046] The object module is used to collect monitoring images of the monitoring data at a preset frequency, identify the object type and relative cable distance in each monitoring image, and generate object impact data based on the object type and the relative cable distance.

[0047] An oxidation module is used to determine the oxidation impact data of the urban cable based on the temperature data, the humidity data, and the oxygen content.

[0048] The vibration module is used to determine the vibration source by calling the corresponding monitoring data according to the digital twin model when the vibration data exceeds a preset threshold, and to generate vibration impact data based on the vibration source and the corresponding current operating data.

[0049] An error module is used to determine the cable power error range based on the cable's required power, the object's influence data, the oxidation influence data, and the vibration influence data; and to generate the cable's operating status based on the cable's current power and the cable power error range.

[0050] The transmission module is used to transmit the object impact data, the oxidation impact data, the vibration source, the vibration impact data, and the cable operating status to the digital twin model for multi-dimensional display.

[0051] The control module is used to shut down the abnormal city cable when the cable is in an abnormal operating state, and to generate a cable control scheme based on the digital twin model.

[0052] Thirdly, the present invention provides an electronic device, including a memory and a processor;

[0053] The memory is used to store computer programs;

[0054] The processor is configured to implement the digital twin management method for urban cables as described in the first aspect when executing the computer program.

[0055] Fourthly, the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the digital twin management method for urban cables as described in the first aspect. Beneficial effects

[0056] The beneficial effects of the digital twin management method, device, equipment, and medium for urban cables of the present invention are:

[0057] By inputting cable parameters, environmental data, and operational data of urban cables into a digital twin model, a highly realistic and dynamically responsive digital twin model of urban cables can be constructed to intuitively and in real-time display the current status of the urban cable system. Secondly, by acquiring monitoring images at a preset frequency, identifying the types of objects and their relative distances to the cables in each image, and generating object impact data based on these object types and relative cable distances, the impact of external factors, such as tree contact and animal intrusion, on cable safety can be quickly identified and assessed. The distance between these objects and the cables and the potential degree of harm can be accurately determined, facilitating the management and control of urban cables. Then, based on environmental data—temperature, humidity, and oxidation impact data determined by oxygen content—potential cable aging problems can be detected early, allowing for management measures to be taken before actual failures occur, significantly reducing the risk of large-scale power outages due to cable faults. Furthermore, when vibration data exceeds a preset threshold, relevant monitoring data is retrieved to accurately locate the vibration source, thereby generating vibration impact data combined with the current operational data, providing a reliable basis for subsequent management of urban cables. By analyzing cable power demand, object influence data, oxidation influence data, and vibration influence data, the cable power error range is determined, making the actual cable power predictable under these influences. The object influence data, oxidation influence data, vibration source data, vibration influence data, and cable operating status are then transmitted to a digital twin model for multi-dimensional visualization. This means that within the constructed digital twin model, cable power exists within a predictable and controllable range. Managers are aware of the current cable operating status under various influencing factors and the corresponding influence data, thereby improving the management capabilities for urban cables. When a cable's operating status is abnormal, it indicates that the current cable power is outside the error range, indicating a problem unpredictable by the digital twin model. In such cases, the faulty cable must be promptly shut down and isolated to prevent the fault from spreading and ensure the normal operation of other cables. Simultaneously, based on the digital twin model, cable control plans can be quickly generated, providing maintenance teams with intuitive fault locations, impact ranges, and repair suggestions, significantly shortening fault diagnosis and recovery time and significantly improving the management capabilities for urban cables. Attached Figure Description

[0058] Figure 1 is a flowchart illustrating the digital twin management and control method for urban cables provided in an embodiment of the present invention;

[0059] Figure 2 is a schematic diagram of the structure of the digital twin management and control device for urban cables provided in an embodiment of the present invention;

[0060] Figure 3 is a schematic diagram of the structure of the electronic device provided in an embodiment of the present invention. Embodiments of the present invention

[0061] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Although some embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the present invention. It should be understood that the accompanying drawings and embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of protection of the present invention.

[0062] It should be understood that the various steps described in the method embodiments of the present invention may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present invention is not limited in this respect.

[0063] The term "comprising" and its variations as used herein are open-ended, meaning "including but not limited to"; the term "based on" means "at least partially based on"; the term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments"; and the term "optionally" means "optional embodiments". Definitions of other terms will be given in the following description. It should be noted that the concepts of "first," "second," etc., mentioned in this invention are used only to distinguish different devices, modules, or units, and are not intended to limit the order of functions performed by these devices, modules, or units or their interdependencies.

[0064] It should be noted that the terms "a" and "a plurality of" used in this invention are illustrative rather than restrictive. Those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0065] The names of the messages or information exchanged between the multiple devices in the embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of these messages or information.

[0066] To address the problems existing in the aforementioned related technologies, this embodiment provides a digital twin management and control method, device, equipment, and medium for urban cables.

[0067] As shown in Figure 1, an embodiment of the present invention provides a digital twin management and control method for urban cables, comprising:

[0068] S1. Based on the obtained cable parameters, environmental data, and operational data of the urban cable, construct a digital twin model of the urban cable; wherein, the environmental data includes monitoring data, temperature data, humidity data, oxygen content, and vibration data, and the operational data includes current operational data, cable power demand, and cable current power.

[0069] Specifically, based on IoT and sensor technologies, environmental and operational data of urban cables are collected, and big data technology is used to obtain cable parameters. These parameters include basic cable specifications such as cable type, dimensions, laying method, and node data. Environmental data includes monitoring data (temperature, humidity, and oxygen content within a specific area), and vibration data (vibration fluctuations within a specific area). It should be noted that the area range varies depending on the type of environmental data. Cable power requirement refers to the power the cable should transmit, and current cable power refers to the power the cable is currently transmitting. Using cable parameters, environmental data, and operational data, a digital twin model of the urban cable can be constructed to clearly and intuitively display these parameters, facilitating subsequent processing and management. For example, corresponding models can be constructed based on cable parameters, environmental data, and operational data, such as 3D models, electrical models, thermodynamic models, and aging models, and then combined to build a digital twin model.

[0070] S2, collect monitoring images of the monitoring data at a preset frequency, identify the object type and relative cable distance in each monitoring image, and generate object impact data based on the object type and the relative cable distance.

[0071] Specifically, the preset frequency is set according to actual conditions and needs, for example, by day, hour, minute, or second, or synchronously set according to the frame rate of the monitoring data. The relative cable distance refers to the shortest distance between an object and the cable. Image recognition and image processing technologies are used to identify the type of object and its relative cable distance in each monitoring image, and object impact data is generated based on the object type and relative cable distance. This object impact data refers to the degree of influence of different objects on cable operation at different distances.

[0072] S3, Based on the temperature data, humidity data, and oxygen content, determine the oxidation impact data of the urban cable.

[0073] Specifically, due to prolonged operation, cables gradually oxidize, which affects their performance. The temperature, humidity, and oxygen content of the surrounding environment significantly influence the degree of oxidation. Deep learning models, machine learning models, or convolutional neural networks can be used to predict the impact of urban cable oxidation based on temperature, humidity, and oxygen content data.

[0074] In one embodiment, after determining the oxidation impact data of the urban cable based on the temperature data, the humidity data, and the oxygen content, the method further includes:

[0075] Based on the oxidation impact data and historical operating data, future operating prediction data is generated;

[0076] Specifically, a convolutional neural network can be used to generate future operational prediction data based on the prediction formula, according to the oxidation impact data and historical operational data. The prediction formula includes: Y(t)=Y0·exp(λ·t+β1·∫Tdt+β2·∫Hdt+β3·∫O x dt);

[0077] Where Y(t) represents the predicted future operation data after time t, Y0 represents the initial performance index, λ represents the base oxidation rate, β1 represents the temperature oxidation rate, T represents the temperature data, β2 represents the humidity oxidation rate, H represents the humidity data, β3 represents the oxygen content oxidation rate, and Ox represents the oxygen content. The base oxidation rate, temperature oxidation rate, humidity oxidation rate, and oxygen content oxidation rate can be derived from actual data and convolutional neural networks.

[0078] S4. When the vibration data is greater than a preset threshold, the corresponding monitoring data is called according to the digital twin model to determine the vibration source, and vibration impact data is generated according to the vibration source and the corresponding current running data.

[0079] Specifically, the preset threshold is the minimum vibration frequency that affects cable operation. Vibration impact data refers to the degree of impact on cable operation within the time of vibration occurrence. When the vibration data exceeds the preset threshold, it indicates that the vibration will affect cable operation. Therefore, based on the digital twin model, the corresponding monitoring data needs to be called to identify objects near the vibration data. If the vibration source is identified as human activity, then the person in the monitoring video is tracked using target detection and tracking algorithms to establish their movement trajectory. Then, a deep learning model is used to analyze the object's movement trajectory, identify its different actions and behaviors, and combine it with a posture estimation algorithm to analyze the human's posture and actions, understand its behavioral characteristics, classify the detected object behaviors, determine human activity, and finally generate vibration impact data based on human activity and current operating data.

[0080] S5. Determine the cable power error range based on the cable power requirement, the object influence data, the oxidation influence data, and the vibration influence data; and generate the cable operating status based on the current cable power and the cable power error range.

[0081] Specifically, since environmental factors can significantly affect the performance of cables during operation, in order to make the cable operating status traceable and predictable in the digital twin model, a predictive model is used to determine the cable power error range by using cable power demand data, object influence data, oxidation influence data, and vibration influence data. This allows managers to know the current cable operating status and understand why the cable has not reached its power demand, thereby increasing their control capabilities.

[0082] S6, the object impact data, the oxidation impact data, the vibration source, the vibration impact data, and the cable operating status are transmitted to the digital twin model for multi-dimensional display.

[0083] Specifically, after transmitting the data on the impact of objects, oxidation, vibration sources, vibration, and cable operation status to the digital twin model, the digital twin model provides a multi-dimensional display of these data. This multi-dimensional display includes one-dimensional text, two-dimensional sound, three-dimensional video, and animation, enabling managers to clearly and intuitively understand the cable operation status and its influencing factors, thus facilitating management.

[0084] S7. When the cable is in an abnormal operating state, shut down the abnormal city cable and generate a cable control scheme based on the digital twin model.

[0085] Specifically, when the current power of the cable is outside the cable power error range, the cable operation status is determined to be abnormal. When the cable operation status is abnormal, the abnormal city cable is shut down. Based on the digital twin model, a cable control plan is generated and displayed in the digital twin model to show the operation status of the controlled cable, so as to provide a clear and intuitive control plan, assist managers in making decisions on cable control, and reduce the consequences and losses caused by abnormal operation in a timely manner.

[0086] By inputting cable parameters, environmental data, and operational data of urban cables into a digital twin model, a highly realistic and dynamically responsive digital twin model of urban cables can be constructed to intuitively and in real-time display the current status of the urban cable system. Secondly, by acquiring monitoring images at a preset frequency, identifying the types of objects and their relative distances to the cables in each image, and generating object impact data based on these object types and relative cable distances, the impact of external factors, such as tree contact and animal intrusion, on cable safety can be quickly identified and assessed. The distance between these objects and the cables and the potential degree of harm can be accurately determined, facilitating the management and control of urban cables. Then, based on environmental data—temperature, humidity, and oxidation impact data determined by oxygen content—potential cable aging problems can be detected early, allowing for management measures to be taken before actual failures occur, significantly reducing the risk of large-scale power outages due to cable faults. Finally, based on the oxidation impact data and historical operational data, future operational prediction data can be generated, clearly demonstrating the impact of oxidation problems on cable operational data, facilitating advance planning of cable usage. Furthermore, when vibration data exceeds a preset threshold, relevant monitoring data is retrieved to accurately locate the vibration source. This data, combined with the current operational data, generates vibration impact data, providing a reliable basis for subsequent management of urban cables. By using cable power demand, object impact data, oxidation impact data, and vibration impact data, the cable power error range is determined, making the actual cable power predictable under various impact data. The object impact data, oxidation impact data, vibration source data, vibration impact data, and cable operating status are transmitted to a digital twin model for multi-dimensional display. In other words, under the constructed digital twin model, cable power exists within a predictable and controllable range. Managers are aware of the current cable operating status under various influencing factors and the various impact data under the current operating status, thereby improving the management capability of urban cables. When a cable is in an abnormal operating state, it indicates that the current power of the cable is outside the cable power error range. This indicates that the cable has encountered an unpredictable problem in the digital twin model. It is necessary to shut down and isolate the faulty cable in a timely manner to prevent the fault from spreading and to ensure the normal operation of other parts of the cable. At the same time, based on the digital twin model, cable control schemes can be generated quickly, providing the maintenance team with intuitive fault location, impact range and repair suggestions, significantly shortening fault diagnosis and recovery time and significantly improving the management and control capabilities of urban cables.

[0087] Optionally, generating object impact data based on the object type and the relative cable distance includes:

[0088] Based on the type of object and the relative cable distance, physical influence factors and electrical influence factors are generated using physical influence formulas and electrical influence formulas, respectively. The physical influence formula includes: PF = h(k) * f(d);

[0089] Wherein, PF is the physical influence factor, h(k) is the risk coefficient function determined according to the object type, k is the object type, f(d) is the risk growth function that varies with the relative cable distance, and d is the relative cable distance;

[0090] The electrical influence formula includes:

[0091] Wherein, EF is the electrical influence factor, g(d) is the degree of electrical interference of conductive objects as the relative cable distance changes, Object non-conduction is a non-conductive object, and Objects conduct electricity is a conductive object;

[0092] Based on the physical influence factor and the electrical influence factor, the comprehensive influence formula is used to generate the object's influence data. The comprehensive influence formula includes: IS = w1 × PF + w2 × EF;

[0093] Wherein, IS represents the object influence data, w1 represents the weighting coefficient of the physical influence factor, and w2 represents the weighting coefficient of the electrical influence factor.

[0094] Specifically, since different objects have different material hardness, magnetism, and density, the potential physical damage to cables varies, and since different objects have different electrical properties, their electrical impact on cables also varies. Therefore, based on the physical and electrical characteristics of different objects, physical influence factors and electrical influence formulas corresponding to them are provided to accurately determine the object influence data. Among them, the risk coefficient function determined according to the type of object, the risk growth function that varies with the relative cable distance, the degree of electrical interference of the conductive object with the relative cable distance, and each weight can be obtained through experiments according to the actual situation.

[0095] Optionally, determining the oxidation impact data of the urban cable based on the temperature data, the humidity data, and the oxygen content includes:

[0096] Based on the cable parameters, determine the cable type;

[0097] When the urban cable is an unsheathed cable, a first oxidation formula is used to generate the oxidation effect data based on the temperature data, humidity data, and oxygen content. The first oxidation formula includes:

[0098] Wherein, O represents the oxidation effect data, A represents the initial constant, Ea represents the oxidation rate, R represents the ideal gas constant, T represents the temperature data, H represents the humidity data, m represents the humidity-induced oxidation rate, Ox represents the oxygen content, and n represents the oxygen-induced oxidation rate.

[0099] When the urban cable is a sheathed cable, the oxidation effect data is generated using a second oxidation formula, which includes:

[0100] Where P represents the sheath data, and 1>P>0, and q represents the sheath protection efficiency, and q>1.

[0101] Specifically, due to different urban cable laying methods, their structures also differ. Urban cables laid underground or at low altitudes generally have protective sheaths, while urban cables laid at high altitudes do not. Therefore, when the urban cable is an unsheathed cable, the first oxidation formula is used to generate the oxidation effect data based on the temperature data, humidity data, and oxygen content. When the urban cable is a sheathed cable, the second oxidation formula is used to generate the oxidation effect data. Here, the initial constant A can be considered the initial rate, that is, the initial rate of the oxidation reaction under given conditions. Its value depends on the properties of the cable material and environmental conditions and needs to be determined experimentally. The oxidation rate Ea represents the energy threshold for the oxidation reaction to occur, affecting the sensitivity of the oxidation rate to temperature, and is also determined experimentally.

[0102] Optionally, determining the cable power error range based on the cable's required power, the object's influence data, the oxidation's influence data, and the vibration's influence data includes:

[0103] Based on the cable power requirement, the object influence data, the oxidation influence data, and the vibration influence data, the minimum power value is determined using an error range formula, which includes: Pmin=(Wi*IS+Wo*O+Wf*F)*Pe*K;

[0104] Wherein, Pmin is the minimum power value, Wi is the object influence weight, IS is the object influence data, Wo is the oxidation influence weight, O is the oxidation influence data, Wf is the vibration influence weight, F is the vibration influence data, Pe is the cable demand power, and K is the correction coefficient;

[0105] The cable power error range is generated based on the minimum power value and the cable power requirement.

[0106] Specifically, the minimum power value can be determined based on the error range formula. Since each influencing factor in the formula has a weight, it reflects their relative importance in different scenarios. For example, if vibration is the main problem in a certain operating environment, while oxidation and object interference have a minor impact, then vibration can be given a higher weight, and the weights of the other two factors can be reduced accordingly to improve the accuracy of obtaining the minimum power value. Then, the minimum power value is used as the lower limit of the cable power error range, and the cable's required power is used as the upper limit of the cable power error range, thus obtaining the cable power error range.

[0107] Optionally, generating a cable control scheme based on the digital twin model includes:

[0108] Based on the digital twin model, the cable parameters of the abnormal city cable are called to generate the location of the faulty cable;

[0109] Traverse the idle city cables within the preset area of ​​the faulty cable location and extract the idle cable parameters of the idle city cables;

[0110] Based on the parameters of the idle cable and the power demand of the cable, an optimization algorithm is used to generate the cable control scheme.

[0111] Specifically, based on the digital twin model, the cable parameters of the malfunctioning city cable are retrieved to generate the fault cable location. Then, idle city cables within a preset area of ​​the fault cable location are traversed, and their idle cable parameters are extracted. The objective is defined as minimizing service interruption time, economic losses, and impact on grid stability caused by the cable fault, while also considering repair costs and resource allocation efficiency. An objective function is set. Then, in the digital twin model, a set of random control strategies is initialized as an initial population. Each strategy includes different maintenance sequences, load redistribution schemes, and backup line activation schemes. A fitness function is designed to evaluate the quality of each strategy; higher fitness indicates a better strategy. The fitness function can be calculated based on the objective function, while also considering factors such as execution time and resource consumption. A genetic operation is then performed for iterative evolution. When the stopping condition is met, the strategy with the highest fitness is selected from the current population as the final cable control scheme.

[0112] Optionally, constructing a digital twin model of the urban cable based on the acquired cable parameters, environmental data, and operational data includes:

[0113] Obtain the city map corresponding to the city cable;

[0114] Based on the cable parameters and the city map, a 3D model of the cable is constructed; based on the environmental data, an environmental model is constructed; based on the operational data, an electrical model is constructed.

[0115] The cable 3D model, the environment model, and the electrical model are input into the digital twin platform to construct the digital twin model.

[0116] Specifically, the process involves acquiring a city map corresponding to the urban cable, constructing a 3D model of the cable using CAD or GIS software based on the cable parameters and the city map, building an environmental model (such as a thermodynamic model or aging model) based on environmental data, and constructing an electrical model based on operational data. These three-dimensional cable model, environmental model, and electrical model are then input into a digital twin platform to construct a digital twin model. After constructing the digital twin model, an association is established between the monitoring equipment and the digital twin model based on the node information of the cable parameters. The digital twin model has a calling interface, which is used to retrieve monitoring data when needed.

[0117] Optionally, the step of acquiring monitoring images of the monitoring data at a preset frequency and identifying the type of object and relative cable distance in each monitoring image includes:

[0118] The monitoring data is collected at the preset frequency to form monitoring images, and an object detection algorithm is used to mark all objects in the monitoring images.

[0119] Extract the image features corresponding to the object, classify the object based on the image features using an image classification algorithm, and generate the object category;

[0120] The pixel size is determined based on the cable parameters and the cable dimensions in the monitoring image;

[0121] The relative cable distance is determined based on the pixel size.

[0122] Specifically, monitoring images are collected at a preset frequency, and an object detection algorithm is used to mark all objects in the monitoring images. Image features corresponding to the objects are extracted, and based on the image features, they are classified according to an image classification algorithm to generate object types. The pixel size is determined based on the cable parameters and the cable size in the monitoring images. The relative cable distance is determined based on the pixel size. This can accurately determine the object type and the relative cable distance, which is convenient for subsequent management and control of urban cables.

[0123] As shown in Figure 2, an embodiment of the present invention provides a digital twin management and control device 200 for urban cables, comprising:

[0124] The construction module 210 is used to construct a digital twin model of the urban cable based on the acquired cable parameters, environmental data, and operational data; wherein, the environmental data includes monitoring data, temperature data, humidity data, oxygen content, and vibration data, and the operational data includes current operational data, cable power demand, and current cable power.

[0125] The object module 220 is used to collect monitoring images of the monitoring data at a preset frequency, identify the object type and relative cable distance in each monitoring image, and generate object impact data based on the object type and the relative cable distance.

[0126] Oxidation module 230 is used to determine the oxidation impact data of the urban cable based on the temperature data, the humidity data, and the oxygen content;

[0127] The vibration module 240 is used to determine the vibration source by calling the corresponding monitoring data according to the digital twin model when the vibration data is greater than a preset threshold, and to generate vibration impact data based on the vibration source and the corresponding current operating data.

[0128] Error module 250 is used to determine the cable power error range based on the cable power demand, the object influence data, the oxidation influence data, and the vibration influence data; and to generate the cable operating status based on the current cable power and the cable power error range.

[0129] Transmission module 260 is used to transmit the object impact data, the oxidation impact data, the vibration source, the vibration impact data, and the cable operating status to the digital twin model for multi-dimensional display;

[0130] The control module 270 is used to shut down the abnormally operating city cable when the cable's operating status is abnormal, and to generate a cable control scheme based on the digital twin model. Optionally,

[0131] As shown in Figure 3, an electronic device 300 provided in this embodiment of the invention includes a memory 310 and a processor 320; the memory 310 is used to store a computer program; the processor 320 is used to implement the digital twin management and control method for urban cables as described above when the computer program is executed.

[0132] Alternatively, an electronic device 300 includes a memory 310 and a processor 320 coupled to the memory 310; the memory 310 is configured to store a computer program; and the processor 320 is configured to perform the following operations when the computer program is executed:

[0133] Based on the obtained cable parameters, environmental data, and operational data of the urban cable, a digital twin model of the urban cable is constructed; wherein, the environmental data includes monitoring data, temperature data, humidity data, oxygen content, and vibration data, and the operational data includes current operational data, cable power demand, and current cable power.

[0134] The monitoring images of the monitoring data are collected at a preset frequency, the object types and relative cable distances in each monitoring image are identified, and object impact data is generated based on the object types and relative cable distances.

[0135] Based on the temperature data, humidity data, and oxygen content, the oxidation impact data of the urban cable is determined;

[0136] When the vibration data exceeds a preset threshold, the corresponding monitoring data is called according to the digital twin model to determine the vibration source, and vibration impact data is generated based on the vibration source and the corresponding current operating data.

[0137] Based on the cable's required power, the object's influence data, the oxidation influence data, and the vibration influence data, the cable power error range is determined; and based on the cable's current power and the cable power error range, the cable's operating status is generated.

[0138] The object impact data, oxidation impact data, vibration source, vibration impact data, and cable operating status are transmitted to the digital twin model for multi-dimensional display.

[0139] When the cable is in an abnormal operating state, the abnormal city cable is shut down, and a cable control scheme is generated based on the digital twin model.

[0140] This invention provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the digital twin management and control method for urban cables as described above.

[0141] Alternatively, a non-volatile computer-readable storage medium storing a computer program that, when executed by a processor, causes the processor to perform the following operations:

[0142] Based on the obtained cable parameters, environmental data, and operational data of the urban cable, a digital twin model of the urban cable is constructed; wherein, the environmental data includes monitoring data, temperature data, humidity data, oxygen content, and vibration data, and the operational data includes current operational data, cable power demand, and current cable power.

[0143] The monitoring images of the monitoring data are collected at a preset frequency, the object types and relative cable distances in each monitoring image are identified, and object impact data is generated based on the object types and relative cable distances.

[0144] Based on the temperature data, humidity data, and oxygen content, the oxidation impact data of the urban cable is determined;

[0145] When the vibration data exceeds a preset threshold, the corresponding monitoring data is called according to the digital twin model to determine the vibration source, and vibration impact data is generated based on the vibration source and the corresponding current operating data.

[0146] Based on the cable's required power, the object's influence data, the oxidation influence data, and the vibration influence data, the cable power error range is determined; and based on the cable's current power and the cable power error range, the cable's operating status is generated.

[0147] The object impact data, oxidation impact data, vibration source, vibration impact data, and cable operating status are transmitted to the digital twin model for multi-dimensional display.

[0148] When the cable is in an abnormal operating state, the abnormal city cable is shut down, and a cable control scheme is generated based on the digital twin model.

[0149] The present invention will now be described an electronic device 300 that can serve as a server or client of the present invention, which is an example of a hardware device that can be applied to various aspects of the present invention. Electronic device 300 is intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic device 300 can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0150] Electronic device 300 includes a computing unit that can perform various appropriate actions and processes based on a computer program stored in read-only memory (ROM) or a computer program loaded from a storage unit into random access memory (RAM). The RAM may also store various programs and data required for device operation. The computing unit, ROM, and RAM are interconnected via a bus. Input / output (I / O) interfaces are also connected to the bus.

[0151] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc. In this application, the units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of the embodiments of the present invention according to actual needs. Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated units can be implemented in hardware or as software functional units.

[0152] While the present invention has been disclosed above, its scope of protection is not limited thereto. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention, and all such changes and modifications will fall within the scope of protection of the present invention.

Claims

1. A digital twin management and control method for urban cables, characterized in that, include: Based on the obtained cable parameters, environmental data, and operational data of the urban cable, a digital twin model of the urban cable is constructed; wherein, the environmental data includes monitoring data, temperature data, humidity data, oxygen content, and vibration data, and the operational data includes the cable's required power and current cable power; The monitoring images of the monitoring data are collected at a preset frequency, the object types and relative cable distances in each monitoring image are identified, and object impact data is generated based on the object types and relative cable distances. Based on the temperature data, humidity data, and oxygen content, the oxidation impact data of the urban cable is determined; When the vibration data exceeds a preset threshold, the corresponding monitoring data is called according to the digital twin model to determine the vibration source, and vibration impact data is generated based on the vibration source and the corresponding current operating data. Based on the cable's required power, the object's influence data, the oxidation influence data, and the vibration influence data, the cable power error range is determined; and based on the cable's current power and the cable power error range, the cable's operating status is generated. The object impact data, oxidation impact data, vibration source, vibration impact data, and cable operating status are transmitted to the digital twin model for multi-dimensional display. When the cable is in an abnormal operating state, shut down the abnormal city cable and generate a cable control scheme based on the digital twin model; The step of generating object impact data based on the object type and the relative cable distance includes: Based on the type of object and the relative cable distance, physical influence factors and electrical influence factors are generated using physical influence formulas and electrical influence formulas, respectively. The physical influence formulas include: PF = h(k) * f(d); Wherein, PF is the physical influence factor, h(k) is the risk coefficient function determined according to the object type, k is the object type, f(d) is the risk growth function that varies with the relative cable distance, and d is the relative cable distance; The electrical influence formula includes: Wherein, EF is the electrical influence factor, g(d) is the degree of electrical interference of conductive objects as the relative cable distance changes, Object non-conduction is a non-conductive object, and Objects conduct electricity is a conductive object; Based on the physical influence factor and the electrical influence factor, a comprehensive influence formula is used to generate the object's influence data. The comprehensive influence formula includes: IS = w1 × PF + w2 × EF; Wherein, IS represents the object influence data, w1 represents the weighting coefficient of the physical influence factor, and w2 represents the weighting coefficient of the electrical influence factor.

2. The digital twin management and control method for urban cables according to claim 1, characterized in that, The step of determining the oxidation impact data of the urban cable based on the temperature data, the humidity data, and the oxygen content includes: Based on the cable parameters, determine the cable type; When the urban cable is an unsheathed cable, a first oxidation formula is used to generate the oxidation effect data based on the temperature data, humidity data, and oxygen content. The first oxidation formula includes: Wherein, O represents the oxidation effect data, A represents the initial constant, Ea represents the oxidation rate, R represents the ideal gas constant, T represents the temperature data, H represents the humidity data, m represents the humidity-induced oxidation rate, Ox represents the oxygen content, and n represents the oxygen-induced oxidation rate. When the urban cable is a sheathed cable, the oxidation effect data is generated using a second oxidation formula, which includes: Where P represents the sheath data, and 1>P>0, and q represents the sheath protection efficiency, and q>1.

3. The digital twin management and control method for urban cables according to claim 1, characterized in that, The step of determining the cable power error range based on the cable power demand, the object influence data, the oxidation influence data, and the vibration influence data includes: Based on the cable's required power, the data on the impact of the object, the data on the impact of oxidation, and the data on the impact of vibration, a minimum power value is determined using an error range formula. This error range formula includes: Pmin=(Wi*IS+Wo*O+Wf*F)*Pe*K; Wherein, Pmin is the minimum power value, Wi is the object influence weight, IS is the object influence data, Wo is the oxidation influence weight, O is the oxidation influence data, Wf is the vibration influence weight, F is the vibration influence data, Pe is the cable demand power, and K is the correction coefficient; The cable power error range is generated based on the minimum power value and the cable power requirement.

4. The digital twin management and control method for urban cables according to claim 1, characterized in that, The generation of a cable control scheme based on the digital twin model includes: Based on the digital twin model, the cable parameters of the abnormal city cable are called to generate the location of the faulty cable; Traverse the idle city cables within the preset area of ​​the faulty cable location and extract the idle cable parameters of the idle city cables; Based on the parameters of the idle cable and the power demand of the cable, an optimization algorithm is used to generate the cable control scheme.

5. The digital twin management and control method for urban cables according to claim 1, characterized in that, The process of constructing a digital twin model of the urban cable based on the acquired cable parameters, environmental data, and operational data includes: Obtain the city map corresponding to the city cable; Based on the cable parameters and the city map, a 3D model of the cable is constructed; based on the environmental data, an environmental model is constructed; based on the operational data, an electrical model is constructed; the 3D model of the cable, the environmental model, and the electrical model are input into the digital twin platform to construct the digital twin model.

6. The digital twin management and control method for urban cables according to claim 1, characterized in that, The process of acquiring monitoring data at a preset frequency and identifying the type of object and relative cable distance in each monitoring image includes: The monitoring data is collected at the preset frequency to form monitoring images, and an object detection algorithm is used to mark all objects in the monitoring images. Extract the image features corresponding to the object, classify the object based on the image features using an image classification algorithm, and generate the object category; The pixel size is determined based on the cable parameters and the cable dimensions in the monitoring image; The relative cable distance is determined based on the pixel size.

7. A digital twin control device for urban cables, characterized in that, include: A construction module is used to construct a digital twin model of the urban cable based on the acquired cable parameters, environmental data, and operational data; wherein, the environmental data includes monitoring data, temperature data, humidity data, oxygen content, and vibration data, and the operational data includes the cable's required power and current cable power. The object module is used to collect monitoring images of the monitoring data at a preset frequency, identify the object type and relative cable distance in each monitoring image, and generate object impact data based on the object type and the relative cable distance. An oxidation module is used to determine the oxidation impact data of the urban cable based on the temperature data, the humidity data, and the oxygen content. The vibration module is used to determine the vibration source by calling the corresponding monitoring data according to the digital twin model when the vibration data exceeds a preset threshold, and to generate vibration impact data based on the vibration source and the corresponding current operating data. An error module is used to determine the cable power error range based on the cable's required power, the object's influence data, the oxidation influence data, and the vibration influence data; and to generate the cable's operating status based on the cable's current power and the cable power error range. The transmission module is used to transmit the object impact data, the oxidation impact data, the vibration source, the vibration impact data, and the cable operating status to the digital twin model for multi-dimensional display. The control module is used to shut down the abnormal city cable when the cable is in an abnormal operating state, and to generate a cable control scheme based on the digital twin model. The step of generating object impact data based on the object type and the relative cable distance includes: Based on the type of object and the relative cable distance, physical influence factors and electrical influence factors are generated using physical influence formulas and electrical influence formulas, respectively. The physical influence formulas include: PF = h(k) * f(d); Wherein, PF is the physical influence factor, h(k) is the risk coefficient function determined according to the object type, k is the object type, f(d) is the risk growth function that varies with the relative cable distance, and d is the relative cable distance; The electrical influence formula includes: Wherein, EF is the electrical influence factor, g(d) is the degree of electrical interference of conductive objects as the relative cable distance changes, Object non-conduction is a non-conductive object, and Objects conduct electricity is a conductive object; Based on the physical influence factor and the electrical influence factor, a comprehensive influence formula is used to generate the object's influence data. The comprehensive influence formula includes: IS = w1 × PF + w2 × EF; Wherein, IS represents the object influence data, w1 represents the weighting coefficient of the physical influence factor, and w2 represents the weighting coefficient of the electrical influence factor.

8. An electronic device, characterized in that, Including memory and processor; The memory is used to store computer programs; The processor is configured to implement the digital twin management method for urban cables as described in any one of claims 1 to 6 when executing the computer program.

9. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the digital twin management method for urban cables as described in any one of claims 1 to 6.

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