Cable health state assessment method and device, equipment and storage medium

Abstract

The invention discloses a cable health state assessment method, device and equipment and a storage medium, relates to the technical field of power systems and automation thereof, and aims to drive a matter element extension model to realize multi-dimensional index assessment of the cable health state by combining cable multi-dimensional index data collected by a digital sensing layer. And the accuracy of a cable health state evaluation result is greatly improved. The method comprises the following steps: pre-constructing a cable digital twin body, wherein the cable digital twin body is total element holographic mapping of a cable physical entity in a digital virtual space; establishing information interaction between a cable physical entity and a sensor agent by using a digital sensing layer configured by a cable digital twinborn body so as to obtain cable multi-dimensional index data of the cable physical entity; and calling a matter-element extension model in a digital calculation layer configured by the digital twinborn body of the cable to input the multi-dimensional index data of the cable into the matter-element extension model for health state evaluation, and outputting an evaluation result of the health state of the cable.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power systems and their automation, and in particular to a cable health state evaluation method, device, equipment and storage medium. BACKGROUND

[0002] In the power transmission and distribution system, as the core current-carrying equipment, the operation health state of the power cable directly determines whether the power grid can safely, reliably and efficiently operate. With the continuous expansion of the power grid scale and the continuous growth of power demand, accurate control of the cable health state is increasingly critical, and cable health state evaluation as a core link to guide state maintenance work has irreplaceable significance to ensure the safety of the power grid energy transmission channel.

[0003] The commonly used cable health state evaluation methods at present mainly include fuzzy mathematics evaluation method, grey clustering evaluation method, neural network method, etc. These methods can preliminarily judge the cable state to a certain extent, but they mainly focus on single type indicators, have the problem of missing evaluation dimensions, so that the evaluation results cannot fully reflect the overall health status of the cable, and it is difficult to meet the requirements of safe and stable operation of the power system. SUMMARY

[0004] Therefore, the present application provides a cable health state evaluation method, device, equipment and storage medium, which mainly aims to solve the problem that the existing cable health state evaluation methods mainly focus on single type indicators, have the problem of missing evaluation dimensions, so that the evaluation results cannot fully reflect the overall health status of the cable, and it is difficult to meet the requirements of safe and stable operation of the power system.

[0005] According to a first aspect of the present application, a cable health state evaluation method is provided, comprising: previously constructing a cable digital twin, the cable digital twin being a full-element holographic mapping of the cable physical entity in a digital virtual space; using a digital perception layer configured by the cable digital twin to establish information interaction between the cable physical entity and a sensor intelligent agent to obtain cable multi-dimensional index data of the cable physical entity; calling a matter-element extension model in a digital calculation layer configured by the cable digital twin to input the cable multi-dimensional index data into the matter-element extension model for health state evaluation, and outputting an evaluation result of the cable health state.

[0006] Further, the digital perception layer includes external digital links and internal digital links; after the cable digital twin is previously constructed, the method further comprises: The external digital link is used to connect to the sensor agent, so that the sensor agent can collect multi-dimensional indicator raw data of the physical entity of the cable, and the multi-dimensional indicator raw data is sent to the internal digital link after being processed by standardization. The standardized data uploaded by the external digital link is distributed to the digital computing layer using the internal digital link to establish a collaborative triggering mechanism among the functional modules within the digital twin.

[0007] Furthermore, the cable digital twin is configured with a digital twin layer, and after the cable digital twin is pre-constructed, the method further includes: Using the cable structure data obtained from video acquisition technology, the digital twin layer constructs a visual 3D model that is consistent with the physical entity of the cable. The visual 3D model depicts the appearance, component composition, and connection relationships between the components of the physical entity of the cable. The visual 3D model includes virtual mapping units of the core components in the physical entity of the cable.

[0008] Furthermore, the cable digital twin is equipped with a digital modeling layer, which has a built-in dual-protocol interaction interface and is equipped with a first communication interaction unit and a second communication interaction unit. The first communication interaction unit establishes a bidirectional information interaction channel between the cable digital twin and the cable physical entity using a first communication standard; after the cable digital twin is pre-constructed, the method further includes: The first communication interaction unit of the digital modeling layer transmits the multi-dimensional operation index data of the cable physical entity to the digital twin, and transmits the control commands of the cable digital twin to the cable physical entity. The second communication interaction unit uses a second communication standard to establish an information interaction channel between the cable digital twin and the external master station system; after the cable digital twin is pre-constructed, the method further includes: The second communication interaction unit of the digital modeling layer transmits the cable health status assessment results and operating status data generated by the cable digital twin to the external master station system, and transmits the scheduling instructions issued by the external master station system to the cable digital twin.

[0009] Furthermore, the digital modeling layer also includes a data parsing unit, and after the pre-construction of the cable digital twin, the method further includes: The data parsing unit of the digital modeling layer performs protocol parsing on the heterogeneous information transmitted by the first communication interaction unit and the second communication interaction unit, and converts it into a standard public information model object and attribute format. The digital modeling layer also includes a message definition unit, and after the pre-construction of the cable digital twin, the method further includes: The message definition unit of the digital modeling layer is used to define standard public information model messages to exchange information between the cable digital twin and the external master station system. The standard public information model messages include at least request messages, response messages, event messages and error messages. The digital modeling layer also includes a model extension unit, and after the pre-construction of the cable digital twin, the method further includes: The model extension unit of the digital modeling layer is used to perform customized extended modeling based on the standard public information model. Specifically, on the basis of the standard public information model, a cable-specific entity class is added. The cable-specific entity class includes the attribute parameters of the core components of the cable and the definition of the relationship between the components. The attribute parameters include at least the material parameters, geometric dimension parameters, electrical performance parameters and operating status parameters of the cable components.

[0010] Furthermore, the digital computing layer subscribes to multi-dimensional cable index data of the physical cable entity from the database of the digital modeling layer: Accordingly, the step of inputting the multi-dimensional index data of the cable into the matter-element extension model for health status assessment and outputting the assessment result of the cable health status includes: Each cable dimension index is pre-divided into multiple health status levels, each health status level corresponds to a classic domain, and the union of all classic domains corresponds to the section domain of the cable dimension index. The correlation function is used to calculate the correlation degree between cable dimension indicators in the multi-cable dimension indicator data and their different health status levels. The assessment result of the cable health status is determined based on the correlation between the cable dimensional indicators and different health status levels.

[0011] Furthermore, determining the assessment result of the cable health status based on the correlation between the cable dimensional indicators and different health status levels includes: Based on the correlation between the cable dimension indicators and different health status levels, the analytic hierarchy process (AHP) is used to compare the two cable dimension indicators to obtain an indicator weight matrix. The elements in the indicator weight matrix represent the relative importance between the two cable dimension indicators. Based on the index weight matrix, the maximum eigenvalue of the index weight matrix and the eigenvector corresponding to the maximum eigenvalue are calculated by the eigenvalue method to obtain a relative weight vector that meets the verification condition. The relative weight vector is obtained by normalizing the eigenvector corresponding to the maximum eigenvalue. The verification condition is that the index weight matrix satisfies the requirement of reasonable weight allocation. Based on the correlation between the relative weight vector and the cable dimension index belonging to different health status levels, calculate the comprehensive correlation between the cable dimension index and each health status level. Based on the principle of maximum correlation, the health status level with the highest comprehensive correlation is determined as the assessment result of the cable's health status.

[0012] According to a second aspect of this application, a cable health status assessment apparatus is provided, comprising: A construction module is used to pre-build a cable digital twin, which is a full-element holographic mapping of the physical entity of the cable in the digital virtual space; The acquisition module is used to establish information interaction between the cable physical entity and the sensor intelligent agent using the digital perception layer configured by the cable digital twin, so as to obtain the cable multi-dimensional index data of the cable physical entity; The evaluation module is used to call the matter-element extension model in the digital computing layer configured in the cable digital twin, so as to input the multi-dimensional index data of the cable into the matter-element extension model for health status evaluation and output the evaluation result of the cable health status.

[0013] Furthermore, the digital sensing layer includes external digital links and internal digital links; the device also includes: The acquisition module is used to connect to the sensor agent via the external digital link after the pre-constructed cable digital twin is built, so as to acquire the original multi-dimensional index data of the cable physical entity through the sensor agent, and send the original multi-dimensional index data to the internal digital link after standardization. The distribution module is used to distribute standardized data uploaded by the external digital link to the digital computing layer using the internal digital link, so as to establish a collaborative triggering mechanism among the functional modules within the digital twin.

[0014] Furthermore, the cable digital twin is configured with a digital twin layer, and after the cable digital twin is pre-constructed, the method further includes: The construction module is used to construct a visual 3D model consistent with the physical entity of the cable using the cable composition data obtained by the digital twin layer based on video acquisition technology after the pre-constructed cable digital twin is built. The visual 3D model depicts the appearance, component composition and connection relationship between components of the physical entity of the cable. The visual 3D model contains virtual mapping units of the core components in the physical entity of the cable.

[0015] Furthermore, the cable digital twin is equipped with a digital modeling layer, which has a built-in dual-protocol interaction interface and is equipped with a first communication interaction unit and a second communication interaction unit. The first communication interaction unit uses a first communication standard to establish a two-way information interaction channel between the cable digital twin and the cable physical entity; the device further includes: The first transmission module is used to transmit the multi-dimensional operating index data of the cable physical entity to the digital twin using the first communication interaction unit of the digital modeling layer after the pre-constructed cable digital twin is built, and to transmit the control commands of the cable digital twin to the cable physical entity. The second communication interaction unit uses a second communication standard to establish an information interaction channel between the cable digital twin and the external master station system; the device further includes: The second transmission module is used to transmit the cable health status assessment results and operating status data generated by the cable digital twin to the external master station system using the second communication interaction unit of the digital modeling layer after the pre-constructed cable digital twin is built, and to transmit the scheduling instructions issued by the external master station system to the cable digital twin.

[0016] Furthermore, the digital modeling layer also includes a data parsing unit, and the device further includes: The parsing module is used to, after the pre-constructed cable digital twin is built, use the data parsing unit of the digital modeling layer to perform protocol parsing on the heterogeneous information transmitted by the first communication interaction unit and the second communication interaction unit respectively, and uniformly convert it into a standard public information model object and attribute format; The digital modeling layer further includes a message definition unit, and the device further includes: The definition module is used to define standard public information model messages using the message definition unit of the digital modeling layer after the pre-constructed cable digital twin is built, so as to exchange information between the cable digital twin and the external master station system through the standard public information model messages. The standard public information model messages include at least request messages, response messages, event messages and error messages. The digital modeling layer further includes a model expansion unit, and the device further includes: An extension module is used to perform customized extended modeling based on the standard public information model using the model extension unit of the digital modeling layer after the pre-constructed cable digital twin is built. Specifically, based on the standard public information model, a cable-specific entity class is added. The specific entity class includes the attribute parameters of the cable core components and the definition of the relationship between the components. The attribute parameters include at least the material parameters, geometric dimension parameters, electrical performance parameters and operating status parameters of the cable components.

[0017] Furthermore, the digital computing layer subscribes to multidimensional cable index data of the physical cable entity from the database of the digital modeling layer; Accordingly, the evaluation module is specifically used for: Each cable dimension index is pre-divided into multiple health status levels, each health status level corresponds to a classic domain, and the union of all classic domains corresponds to the section domain of the cable dimension index. The correlation function is used to calculate the correlation degree between cable dimension indicators in the multi-cable dimension indicator data and their different health status levels. The assessment result of the cable health status is determined based on the correlation between the cable dimensional indicators and different health status levels.

[0018] Furthermore, the evaluation module is specifically used for: Based on the correlation between the cable dimension indicators and different health status levels, the analytic hierarchy process (AHP) is used to compare the two cable dimension indicators to obtain an indicator weight matrix. The elements in the indicator weight matrix represent the relative importance between the two cable dimension indicators. Based on the index weight matrix, the maximum eigenvalue of the index weight matrix and the eigenvector corresponding to the maximum eigenvalue are calculated by the eigenvalue method to obtain a relative weight vector that meets the verification condition. The relative weight vector is obtained by normalizing the eigenvector corresponding to the maximum eigenvalue. The verification condition is that the index weight matrix satisfies the requirement of reasonable weight allocation. Based on the correlation between the relative weight vector and the cable dimension index belonging to different health status levels, calculate the comprehensive correlation between the cable dimension index and each health status level. Based on the principle of maximum correlation, the health status level with the highest comprehensive correlation is determined as the assessment result of the cable's health status.

[0019] According to a third aspect of this application, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method described in the first aspect above.

[0020] According to a fourth aspect of this application, a readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in the first aspect above.

[0021] By employing the above technical solution, this application provides a method, apparatus, device, and storage medium for assessing cable health status. Compared with the existing technology that assesses cable health status based on a single index type using a threshold judgment method, this application pre-constructs a cable digital twin, which is a full-element holographic mapping of the cable physical entity in digital virtual space. The digital perception layer configured with the cable digital twin establishes information interaction between the cable physical entity and the sensor intelligence to obtain multi-dimensional cable index data. The matter-element extension model is invoked in the digital computing layer configured with the cable digital twin to input the multi-dimensional cable index data into the matter-element extension model for health status assessment, and the assessment result of the cable health status is output. The entire process achieves full-element mapping of the physical entity of the cable in the information space through the cable, enabling the static attributes and dynamic operating status of the physical entity of the cable to be accurately reproduced in the virtual information space. Combined with the multi-dimensional index data of the cable collected by the digital perception layer, the matter-element extension model is driven to realize multi-dimensional index evaluation of the cable health status, which greatly improves the accuracy of the cable health status evaluation results. It can not only accurately identify the type and location of the fault that has occurred, but also predict the potential deterioration trend of the cable, providing a basis for the refined operation and maintenance of the cable.

[0022] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0023] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 This is a flowchart illustrating a method for assessing the health status of a cable according to an embodiment of this application; Figure 2 This is an architectural diagram of a cable digital twin provided in an embodiment of this application; Figure 3 This is a schematic diagram of the data interaction logic at each level in a cable digital twin provided in an embodiment of this application; Figure 4 This is an external digital link architecture diagram provided in one embodiment of this application; Figure 5 This is a diagram of the internal digital link architecture provided in one embodiment of this application; Figure 6 This is a digital computing layer architecture diagram provided in an embodiment of this application; Figure 7 yesFigure 1 A schematic diagram of a specific implementation method for step 103; Figure 8 This is a schematic diagram of the process for assessing the health status of an object-element extension model provided in an embodiment of this application; Figure 9 This is a schematic diagram of the structure of a cable health status assessment device provided in an embodiment of this application; Figure 10 This is a schematic diagram of the device structure of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0024] The invention will now be discussed with reference to several exemplary embodiments. It should be understood that these embodiments are described merely to enable those skilled in the art to better understand and thus implement the invention, and are not intended to imply any limitation on the scope of the invention.

[0025] As used herein, the term "comprising" and its variations are to be interpreted as open-ended terms meaning "including but not limited to". The term "based on" is to be interpreted as "at least partially based on". The terms "one embodiment" and "an embodiment" are to be interpreted as "at least one embodiment". The term "another embodiment" is to be interpreted as "at least one other embodiment".

[0026] In related technologies, the main methods for assessing the health status of cables include fuzzy mathematics assessment, grey clustering assessment, and neural network methods. These methods can make a preliminary judgment on the cable status to a certain extent, but they mostly focus on a single type of indicator and have the problem of missing assessment dimensions. As a result, the assessment results cannot fully reflect the overall health status of the cable and are difficult to meet the requirements for safe and stable operation of the power system.

[0027] To address this problem, this embodiment provides a method for assessing the health status of cables, such as... Figure 1 As shown, it includes the following steps: 101. Pre-construct a digital twin of the cable.

[0028] In this embodiment, the cable digital twin is typically a virtual entity built in advance based on the physical entity's design parameters, structural data, performance indicators, and other fundamental data, using technologies such as 3D modeling and data integration, before the cable is put into operation. This preparatory step ensures that the digital twin serves as a virtual mirror image of the cable's physical entity throughout its entire lifecycle, providing a foundation for subsequent data collection, health assessment, and fault early warning.

[0029] The cable digital twin is a holographic mapping of all elements of the physical cable entity in digital virtual space. This holographic mapping covers all key components and operating parameters of the physical cable entity, including but not limited to core components (conductors, insulation, shielding, sheath), auxiliary structures (joints, terminals), environmental parameters (laying environment temperature, humidity, soil corrosivity, etc.), and operating data (voltage, current, loss, etc.), replicating the complete attributes of the physical entity without omissions or blind spots. This holographic mapping ensures that every element and parameter in the digital twin maintains a high degree of consistency with the actual state of the physical cable entity. Any changes in the physical entity are fed back to the digital twin in real time, achieving bidirectional synchronization between the physical and virtual domains.

[0030] It should be noted that the cable digital twin is not a simple three-dimensional visualization model, but a digital twin object that corresponds one-to-one with the physical cable and is linked in real time. It includes the static characteristics of the cable, such as conductor cross-sectional dimensions, insulation material, sheath thickness, and laying path, and can also synchronously map the dynamic operating status of the physical entity, such as real-time temperature, load current, and insulation resistance changes. It is equivalent to a digital substitute of the physical entity in virtual space.

[0031] 102. Using the digital perception layer configured by the cable digital twin, establish information interaction between the cable physical entity and the sensor intelligent entity to obtain multi-dimensional cable index data of the cable physical entity.

[0032] In this embodiment, the cable digital twin is equipped with a digital sensing layer to connect the physical cable entity and the sensor agent. The specific information interaction process is not a simple data transmission, but rather the establishment of a two-way information interaction channel: on the one hand, it supports the sensor agent to upload the collected cable operation data to the digital twin; on the other hand, it supports the digital twin to issue instructions to the sensor agent, realizing the linkage between the physical side and the virtual side.

[0033] The multi-dimensional cable index data encompasses various key parameters reflecting the cable's operating status, including electrical indicators (voltage, current, insulation resistance, dielectric loss), thermal indicators (conductor temperature, sheath temperature, ambient temperature), and mechanical indicators (laying stress, vibration frequency), rather than single-dimensional indicators. This data forms the basis for health status assessments of the cable digital twin. Only by acquiring comprehensive multi-dimensional cable index data can the actual operating status of the physical cable be accurately reproduced in virtual space, supporting the functional implementation of the digital twin.

[0034] 103. In the digital computing layer configured in the cable digital twin, the matter-element extension model is invoked to input the multi-dimensional index data of the cable into the matter-element extension model for health status assessment, and the assessment result of the cable health status is output.

[0035] In this embodiment, the cable digital twin is equipped with a digital computing layer, which serves as the functional core of the cable digital twin and undertakes the task of quantitatively assessing the cable's health status. It has built-in dedicated computing resources to meet the computational requirements of the matter-element extension model, which can ensure the real-time performance and accuracy of the assessment process.

[0036] Specifically, in the process of inputting multi-dimensional cable index data into the matter-element extension model for health status assessment, the cable health status can be defined as the core matter element. A set of matter elements corresponding to the cable health level is constructed based on the multi-dimensional cable index data. In this set, the multi-dimensional cable indexes are defined as matter element features, and the corresponding multi-dimensional cable index data are defined as matter element feature values. Based on this set, the multi-dimensional cable index data is substituted into the set to calculate the correlation between each dimension index and different health levels, thereby quantifying the impact weight of single indicators and indicator combinations on the overall health status. Based on the correlation calculation results, the current health level of the cable is determined according to preset rules, and abnormal dimension indicators affecting the health status are identified.

[0037] It should be noted that the cable health status assessment results are not a simple binary conclusion of pass / fail, but a quantitative report that includes the overall health level, the degree of abnormality of individual indicators, and potential fault risk warnings. To facilitate decision-making for maintenance personnel, the cable health status assessment results can be synchronized to the visualization module of the digital twin or the external master station system. The corresponding assessment results are presented in the visualization module as highlighted annotations on the cable's 3D model, color-coded health levels, and pop-up windows displaying abnormal indicator values. In the external master station system, the results are archived and stored in a standardized model data format.

[0038] The cable health status assessment method provided in this application differs from existing technologies that assess cable health status based on a single indicator type using a threshold judgment method. This application pre-constructs a cable digital twin, which is a full-element holographic mapping of the physical cable entity in a digital virtual space. A digital perception layer configured with the cable digital twin is used to establish information interaction between the physical cable entity and a sensor agent to obtain multi-dimensional cable indicator data. A matter-element extension model is invoked in the digital computing layer configured with the cable digital twin to input the multi-dimensional cable indicator data into the matter-element extension model for health status assessment, and the assessment result of the cable health status is output. The entire process achieves full-element mapping of the physical entity of the cable in the information space through the cable, enabling the static attributes and dynamic operating status of the physical entity of the cable to be accurately reproduced in the virtual information space. Combined with the multi-dimensional index data of the cable collected by the digital perception layer, the matter-element extension model is driven to realize multi-dimensional index evaluation of the cable health status, which greatly improves the accuracy of the cable health status evaluation results. It can not only accurately identify the type and location of the fault that has occurred, but also predict the potential deterioration trend of the cable, providing a basis for the refined operation and maintenance of the cable.

[0039] In practical applications, the architecture of a cable digital twin is as follows: Figure 2 As shown, the operation and maintenance linkage of cable status is realized through the link formed by the physical cable entity, the digital twin of the cable, and the external system. The specific implementation may include, but is not limited to, the following steps: Each sensor agent deployed on the physical cable entity collects multi-dimensional index data of the cable through a wide area communication network and uploads the multi-dimensional index data of the cable to the digital twin of the cable; then, the digital twin of the cable is set up with multiple layers. The digital perception layer receives the multi-dimensional index data of the cable uploaded by the sensor agents, completes the conversion and preprocessing of physical signals to digital signals, the digital twin layer constructs a full-element holographic mapping of the physical cable entity to form a three-dimensional visualization model of the cable, the digital modeling layer parses the perception data layer into the object format of the standard public information model, and realizes protocol adaptation with the external system, and the digital computing layer calls the matter-element extension model to perform calculations on the multi-dimensional index data of the cable and outputs the evaluation results of the cable health status.

[0040] In practical application scenarios, the data interaction logic at each level in a cable digital twin is as follows: Figure 3As shown, a closed loop is achieved through multi-level protocols, encompassing data acquisition of the physical cable entity, processing of the cable digital twin, and linkage with external systems. Specific implementation may include, but is not limited to, the following steps: Telemetry devices deployed on the physical cable entity collect cable operation data and transmit it to the external digital link of the digital sensing layer via the IEC 60870-5-101 / 104 protocol, completing the access of physical data to the digital space; the telemetry data received by the external digital link is transmitted to the database for storage via the internal digital link; simultaneously, the publisher / subscriber mechanism of the Enterprise Service Bus (ESB) enables data distribution within the digital twin, providing data support for subsequent layers; after obtaining multi-dimensional cable indicator data through the internal digital link, the digital twin layer transmits it to the digital modeling layer, enabling the digital modeling layer to comply with IEC 60870-5-101 / 104 and IEC standards. The 61968 protocol and other two types are used to achieve protocol adaptation with the physical side and external systems respectively, and to convert data into standard format. The digital computing layer obtains standard format data from the digital modeling layer and inputs it into the health assessment model to complete the cable health status assessment. The assessment results are fed back to the digital modeling layer through the storage / retrieval link, and synchronized to the health status and external systems. At the same time, the external master system can also subscribe to twin information through the digital modeling layer.

[0041] Specifically, the aforementioned digital perception layer includes external and internal digital links, virtually depicting the information interaction between the cable digital twin and the actual cable, the external master station system, and the information interaction between components within the digital twin. It possesses functions such as acquiring, processing, storing, and publishing cable entity information. Correspondingly, after pre-constructing the cable digital twin, the above method also includes the following steps: The external digital link is used to connect to the sensor agent, so that the sensor agent can collect multi-dimensional indicator raw data of the physical entity of the cable, and the multi-dimensional indicator raw data is sent to the internal digital link after being processed by standardization. The standardized data uploaded by the external digital link is distributed to the digital computing layer using the internal digital link to establish a collaborative triggering mechanism among the functional modules within the digital twin.

[0042] In this embodiment, the external digital link virtually depicts the information interaction between the physical cable and the sensor, as well as the information interaction with the external master station system. Its architecture is as follows: Figure 4 As shown, the physical cable and the sensor transmit energy through an aviation connector. The external digital link acquires telemetry information through the main station front-end and then transmits it to the corresponding virtual aviation connector via wired communication such as fiber optic or Ethernet passive optical network, or 4G / 5G wireless communication.

[0043] In this embodiment, the internal digital link is mainly used for data acquisition, processing and storage, and data publishing within the twin, and its architecture is as follows:Figure 5 As shown. Data acquisition adopts a bottom-up approach, that is, receiving telemetry and external system information from external digital links, which are then processed and stored in the main control unit of the digital twin after passing through the corresponding loops, while also receiving data requests from subscribers; data publishing adopts a top-down approach, that is, publishing data subscribed to by the upper layer of the digital twin.

[0044] Specifically, the aforementioned cable digital twin is configured with a digital twin layer. Correspondingly, after pre-constructing the cable digital twin, the method further includes the following steps: Using the cable structure data acquired through video acquisition technology, the digital twin layer constructs a visualized 3D model that corresponds to the physical cable entity. This visualized 3D model depicts the appearance, component composition, and inter-component connections of the physical cable entity. The visualized 3D model includes virtual mapping units of the core components of the physical cable entity. In this embodiment, the digital twin layer is a virtual representation of the cable's physical appearance, components, and connections. Based on technologies such as 3D laser scanning and video recording, a visual model is constructed that is highly consistent with the physical cable in terms of geometric dimensions, spatial layout, and component composition. In other words, the digital twin layer can create a 3D model of the cable including components such as conductors, insulation layers, and sheaths.

[0045] Specifically, the aforementioned cable digital twin is equipped with a digital modeling layer, which has a built-in dual-protocol interaction interface and is equipped with a first communication interaction unit and a second communication interaction unit. The first communication interaction unit uses a first communication standard to establish a two-way information interaction channel between the cable digital twin and the cable physical entity. Accordingly, after pre-constructing the cable digital twin, the above method further includes the following steps: The first communication interaction unit of the digital modeling layer transmits the multi-dimensional operation index data of the cable physical entity to the digital twin, and transmits the control commands of the cable digital twin to the cable physical entity. The second communication interaction unit uses a second communication standard to establish an information interaction channel between the cable digital twin and the external master station system; correspondingly, after pre-constructing the cable digital twin, the above method also includes the following steps: The second communication interaction unit of the digital modeling layer transmits the cable health status assessment results and operating status data generated by the cable digital twin to the external master station system, and transmits the scheduling instructions issued by the external master station system to the cable digital twin.

[0046] In this embodiment, the digital modeling layer is a model that enables information interaction between the cable digital twin, the actual cable, and the external master station system. As a possible implementation of the first communication interaction unit, the information interaction between the cable digital twin and the actual cable is achieved through the IEC 60870-5-101 / 104 protocol. As a possible implementation of the second communication interaction unit, the information interaction between the cable digital twin and the external master station system is achieved through the IEC 61968 standard.

[0047] Furthermore, to address the issue of incompatibility between heterogeneous information and provide standardized data for cross-level and cross-system collaboration of cable digital twins, the aforementioned digital modeling layer also includes a data parsing unit. Accordingly, after pre-constructing the cable digital twin, the method further includes the following steps: The data parsing unit of the digital modeling layer performs protocol parsing on the heterogeneous information transmitted by the first communication interaction unit and the second communication interaction unit, and converts it into a standard public information model object and attribute format.

[0048] In this embodiment, the transmission of the first communication interaction unit is implemented based on the IEC 60870-5-101 / 104 protocol, while the transmission of the second communication interaction unit is implemented based on the IEC 61968 specification. The two are heterogeneous data. Through protocol parsing and standard common information model format conversion, these differences can be unified into standard common information model object and attribute formats, ensuring that the understanding of data by each level within the cable digital twin is completely consistent.

[0049] Furthermore, in order to establish standardized information exchange and ensure the consistency of information transmission between the cable digital twin and external systems / internal levels, the aforementioned digital modeling layer also includes a message definition unit. Accordingly, after pre-constructing the cable digital twin, the above method also includes the following steps: The message definition unit of the digital modeling layer is used to define standard public information model messages to exchange information between the cable digital twin and the external master station system. The standard public information model messages include at least request messages, response messages, event messages and error messages.

[0050] In this embodiment, the message definition unit defines standard common model messages, which can formulate a standardized language for the interaction between the cable digital twin and the external master station system or internal layers, avoiding information ambiguity caused by differences in message format and field definition between different systems / layers.

[0051] Furthermore, to adapt the standard public information model to the specific characteristics of cable equipment and achieve accurate mapping and cross-system compatibility of cable information, the aforementioned digital modeling layer also includes a model extension unit. Accordingly, after pre-constructing the cable digital twin, the above method also includes the following steps: The model extension unit of the digital modeling layer is used to perform customized extended modeling based on the standard public information model. Specifically, on the basis of the standard public information model, a cable-specific entity class is added. The cable-specific entity class includes the attribute parameters of the core components of the cable and the definition of the relationship between the components. The attribute parameters include at least the material parameters, geometric dimension parameters, electrical performance parameters and operating status parameters of the cable components.

[0052] In this embodiment, the standard common information model is a basic model for all types of equipment in the power system, but it does not provide detailed definitions for the specific characteristics of cables, such as component parameters like conductor structure, insulation material, and sheath type, or attributes related to the laying environment. Here, the model extension unit fills the gaps in the general model by adding cable-specific entity classes and attribute sets, allowing the standard common information model to accurately cover all elements of cable information. For example, the newly added entity classes in the model extension unit can be seen in Table 1 below, and the attributes of the new entity classes can be seen in Tables 2-4.

[0053] Table 1. New Class Attributes Extended by the Cable Standard Public Information Model

[0054] Table 2. Description of CableBaseInfo Class Attributes

[0055] Table 3. Description of CableHealthStatus Class Attributes

[0056] Table 4. Description of CableMeasurement Class Attributes

[0057] Specifically, the aforementioned digital computing layer subscribes to multi-dimensional cable index data of the physical cable entity from the database of the digital modeling layer; its architecture is as follows: Figure 6As shown, a publish-subscribe mechanism is used to achieve data flow linkage between the health assessment model and multiple source databases. On one hand, the digital modeling layer integrates various types of databases, which store standardized data such as basic cable information and operational data. Through the publisher role, it provides unified data distribution to the outside world. On the other hand, the digital computing layer has a built-in matter-element extension model. Through the subscriber role, it obtains multi-dimensional cable indicator data from the publisher in the digital modeling layer. The matter-element extension model completes the cable health status assessment calculation based on this data. The specific process of using the matter-element extension model to assess cable health status is described below: Specifically, such as Figure 7 As shown, step 103 includes the following steps: 201. Pre-classify each cable dimension indicator into multiple health status levels.

[0058] 202. Use correlation functions to calculate the correlation degree between cable dimension indicators in the multi-cable dimension indicator data and their different health status levels.

[0059] 203. Determine the assessment result of the cable health status based on the correlation between the cable dimensional indicators and different health status levels.

[0060] In this embodiment, each health status level corresponds to a classical domain, and the union of all classical domains corresponds to the section domain of the cable dimension index. For example, the section domain of the outer sheath grounding current is (0, ∞). In actual evaluation, a reasonable upper limit can be set according to the actual situation, such as 200A, that is, the section domain is (0, 200).

[0061] For specific cable dimensional index classifications, relevant standards and engineering practice experience can be referenced. Cable health status levels are divided into five levels (Level I: Good, Level II: Normal, Level III: Caution, Level IV: Abnormal, Level V: Severe Abnormal), each level corresponding to a numerical range, i.e., the classic domain. Taking the outer sheath grounding current as an example, the classic domain classifications for outer sheath grounding current are as follows: Level I (≤50A), Level II (50 - 80A), Level III (80 - 100A), Level IV (100 - 120A), Level V (>120A). The classic domain classifications for other indicators are similar; specific values ​​are determined based on standards and practice.

[0062] Accordingly, in determining the assessment result of cable health status based on the correlation between cable dimension indicators and different health status levels, the analytic hierarchy process (AHP) can be used to compare two cable dimension indicators based on their correlation to different health status levels, resulting in an indicator weight matrix. The elements in the indicator weight matrix represent the relative importance between the two cable dimension indicators. Based on the indicator weight matrix, the maximum eigenvalue and the corresponding eigenvector of the indicator weight matrix are calculated using the eigenvalue method to obtain a relative weight vector that meets the verification criteria. The relative weight vector is obtained by normalizing the eigenvector corresponding to the maximum eigenvalue, and the verification criteria are that the indicator weight matrix satisfies a reasonable weight allocation. Based on the correlation between the relative weight vector and the cable dimension indicators and their different health status levels, the comprehensive correlation between the cable dimension indicators and each health status level is calculated. According to the principle of maximum correlation, the health status level with the highest comprehensive correlation is determined as the assessment result of the cable health status.

[0063] In practical applications, the process for assessing the health status of the matter-element extension model can be found in [reference needed]. Figure 8 As shown, in Figure 8 In this process, the digital computing layer subscribes to the database in the digital modeling layer to obtain multi-dimensional cable index data, including outer sheath grounding current, intermediate joint partial discharge, cable trench grounding resistance, relative temperature difference of cable terminals, phase-to-phase temperature difference of terminal body, cable sealing sleeve temperature, voltage deviation, and three-phase imbalance. These eight data points that need to be subscribed to constitute eight indices. These eight indices are used to construct an eight-dimensional basic matter element, as shown in the following expression:

[0064] in, arrive These are evaluation indicators. arrive These are the indicator data for each dimension of the cable.

[0065] To calculate the correlation degree of each indicator belonging to each evaluation level using the correlation function, please refer to the following expression:

[0066] Where x is the measured value of the indicator. For classical domains, For the section domain, For classical domains Length, Represents the distance from point x to the classical field. distance, Represents the distance from point x to the node region. The distance between the indicators and the five health levels can be calculated based on the correlation function above. (i is the indicator number, j is the health level number).

[0067] Furthermore, the analytic hierarchy process (AHP) was used to perform pairwise comparisons of the eight indicators, constructing an 8×8 index weight matrix. To determine the indicator weights. In the indicator weight matrix A... The value represents the importance of the i-th indicator relative to the j-th indicator, where 1 indicates equal importance, 3 indicates slightly important, 5 indicates significantly important, 7 indicates strongly important, and 9 indicates extremely important. 2, 4, 6, and 8 are the median values ​​of adjacent scales and satisfy the following condition: , , .

[0068] After obtaining the indicator weight matrix, the largest eigenvalue of the indicator weight matrix is ​​calculated using the eigenvalue method. The corresponding eigenvectors are then normalized to obtain the relative weight vectors. Then, a consistency check is performed on the relative weight vector, which can be referred to in the following expression: ,

[0069] Where RI is the average random consistency index, and when n=8, RI=1.41. Specifically, if Then the indicator weight matrix is ​​determined to satisfy the reasonable weight allocation, if If the determination of the indicator weight matrix does not satisfy the reasonable allocation of weights, the elements of the indicator weight matrix need to be adjusted until the consistency test is passed.

[0070] Furthermore, the correlation between the relative weight vector and the cable dimension index at different health status levels, and the comprehensive correlation between the cable dimension index and each health status level, can be calculated using the following expression:

[0071] Based on the principle of maximum correlation, the health status level with the highest comprehensive correlation is selected as the assessment result of the cable's health status, which can be referred to as the following expression:

[0072] In practical applications, multiple sensors are used to collect multi-dimensional indicators such as temperature, partial discharge, and power quality, overcoming the limitations of traditional methods that rely on a single indicator. This allows for a comprehensive characterization of the overall health status of the cable. In field testing, for a long-running cable, data from eight indicators (86.7, 92, 3.5, 15, 2.4, 91, 7.5%, 1.4%) were collected. The health status level with the highest comprehensive correlation was identified as Level V, indicating a severely abnormal state. This accurately reflects the actual situation of aging and other problems caused by environmental factors in long-running cables, effectively avoiding the biased assessment caused by a single indicator.

[0073] In practical applications, the five health status levels mentioned above can be correlated with quantitative correlation values. This not only clarifies the cable health level but also reflects the health differences within the same level through the correlation value, helping maintenance personnel to more accurately judge the degree of cable degradation.

[0074] Furthermore, as a specific implementation of the above method, embodiments of this application provide a cable health status assessment device, such as... Figure 9 As shown, the device includes: a construction module 31, an acquisition module 32, and an evaluation module 33.

[0075] Module 31 is used to pre-build a cable digital twin, which is a full-element holographic mapping of the physical entity of the cable in the digital virtual space; The acquisition module 32 is used to establish information interaction between the cable physical entity and the sensor intelligent agent using the digital perception layer configured by the cable digital twin, so as to obtain the cable multi-dimensional index data of the cable physical entity; The evaluation module 33 is used to call the matter-element extension model in the digital computing layer configured in the cable digital twin, so as to input the multi-dimensional index data of the cable into the matter-element extension model for health status evaluation and output the evaluation result of the cable health status.

[0076] The cable health status assessment device provided in this invention, compared with the existing technology that assesses cable health status based on a single index type using a threshold judgment method, pre-constructs a cable digital twin, which is a full-element holographic mapping of the physical cable entity in a digital virtual space; uses a digital perception layer configured with the cable digital twin to establish information interaction between the physical cable entity and the sensor intelligence to obtain multi-dimensional index data of the physical cable entity; and calls a matter-element extension model in the digital computing layer configured with the cable digital twin to input the multi-dimensional index data of the cable into the matter-element extension model for health status assessment, and outputs the assessment result of the cable health status. The entire process achieves full-element mapping of the physical entity of the cable in the information space through the cable, enabling the static attributes and dynamic operating status of the physical entity of the cable to be accurately reproduced in the virtual information space. Combined with the multi-dimensional index data of the cable collected by the digital perception layer, the matter-element extension model is driven to realize multi-dimensional index evaluation of the cable health status, which greatly improves the accuracy of the cable health status evaluation results. It can not only accurately identify the type and location of the fault that has occurred, but also predict the potential deterioration trend of the cable, providing a basis for the refined operation and maintenance of the cable.

[0077] In specific application scenarios, the digital sensing layer includes external digital links and internal digital links; the device also includes: The acquisition module is used to connect to the sensor agent via the external digital link after the pre-constructed cable digital twin is built, so as to acquire the original multi-dimensional index data of the cable physical entity through the sensor agent, and send the original multi-dimensional index data to the internal digital link after standardization. The distribution module is used to distribute standardized data uploaded by the external digital link to the digital computing layer using the internal digital link, so as to establish a collaborative triggering mechanism among the functional modules within the digital twin.

[0078] In specific application scenarios, the cable digital twin is configured with a digital twin layer. After the cable digital twin is pre-constructed, the method further includes: The construction module is used to construct a visual 3D model consistent with the physical entity of the cable using the cable composition data obtained by the digital twin layer based on video acquisition technology after the pre-constructed cable digital twin is built. The visual 3D model depicts the appearance, component composition and connection relationship between components of the physical entity of the cable. The visual 3D model contains virtual mapping units of the core components in the physical entity of the cable.

[0079] In specific application scenarios, the cable digital twin is configured with a digital modeling layer, which has a built-in dual-protocol interaction interface and is equipped with a first communication interaction unit and a second communication interaction unit. The first communication interaction unit uses a first communication standard to establish a two-way information interaction channel between the cable digital twin and the cable physical entity; the device further includes: The first transmission module is used to transmit the multi-dimensional operating index data of the cable physical entity to the digital twin using the first communication interaction unit of the digital modeling layer after the pre-constructed cable digital twin is built, and to transmit the control commands of the cable digital twin to the cable physical entity. The second communication interaction unit uses a second communication standard to establish an information interaction channel between the cable digital twin and the external master station system; the device further includes: The second transmission module is used to transmit the cable health status assessment results and operating status data generated by the cable digital twin to the external master station system using the second communication interaction unit of the digital modeling layer after the pre-constructed cable digital twin is built, and to transmit the scheduling instructions issued by the external master station system to the cable digital twin.

[0080] In specific application scenarios, the digital modeling layer further includes a data parsing unit, and the device further includes: The parsing module is used to, after the pre-constructed cable digital twin is built, use the data parsing unit of the digital modeling layer to perform protocol parsing on the heterogeneous information transmitted by the first communication interaction unit and the second communication interaction unit respectively, and uniformly convert it into a standard public information model object and attribute format; The digital modeling layer further includes a message definition unit, and the device further includes: The definition module is used to define standard public information model messages using the message definition unit of the digital modeling layer after the pre-constructed cable digital twin is built, so as to exchange information between the cable digital twin and the external master station system through the standard public information model messages. The standard public information model messages include at least request messages, response messages, event messages and error messages. The digital modeling layer further includes a model expansion unit, and the device further includes: An extension module is used to perform customized extended modeling based on the standard public information model using the model extension unit of the digital modeling layer after the pre-constructed cable digital twin is built. Specifically, based on the standard public information model, a cable-specific entity class is added. The specific entity class includes the attribute parameters of the cable core components and the definition of the relationship between the components. The attribute parameters include at least the material parameters, geometric dimension parameters, electrical performance parameters and operating status parameters of the cable components.

[0081] In specific application scenarios, the digital computing layer subscribes to multi-dimensional cable index data of the physical cable entity from the database of the digital modeling layer; Accordingly, the evaluation module is specifically used for: Each cable dimension index is pre-divided into multiple health status levels, each health status level corresponds to a classic domain, and the union of all classic domains corresponds to the section domain of the cable dimension index. The correlation function is used to calculate the correlation degree between cable dimension indicators in the multi-cable dimension indicator data and their different health status levels. The assessment result of the cable health status is determined based on the correlation between the cable dimensional indicators and different health status levels.

[0082] In specific application scenarios, the evaluation module is further used for: Based on the correlation between the cable dimension indicators and different health status levels, the analytic hierarchy process (AHP) is used to compare the two cable dimension indicators to obtain an indicator weight matrix. The elements in the indicator weight matrix represent the relative importance between the two cable dimension indicators. Based on the index weight matrix, the maximum eigenvalue of the index weight matrix and the eigenvector corresponding to the maximum eigenvalue are calculated by the eigenvalue method to obtain a relative weight vector that meets the verification condition. The relative weight vector is obtained by normalizing the eigenvector corresponding to the maximum eigenvalue. The verification condition is that the index weight matrix satisfies the requirement of reasonable weight allocation. Based on the correlation between the relative weight vector and the cable dimension index belonging to different health status levels, calculate the comprehensive correlation between the cable dimension index and each health status level. Based on the principle of maximum correlation, the health status level with the highest comprehensive correlation is determined as the assessment result of the cable's health status.

[0083] It should be noted that other corresponding descriptions of the functional units involved in the cable health status assessment device provided in this embodiment can be found in [reference needed]. Figures 1-8 The corresponding descriptions in [the document] will not be repeated here.

[0084] Based on the above, Figures 1-8Accordingly, this application embodiment also provides a storage medium storing a computer program thereon, which, when executed by a processor, implements the above-described method. Figures 1-8 The method for assessing the health status of cables is shown.

[0085] Based on this understanding, the technical solution of this application can be embodied in the form of a software product. The software product can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, or portable hard drive), and includes several instructions to cause a computer device (such as a personal computer, server, or network device) to execute the methods described in the various implementation scenarios of this application.

[0086] Based on the above, Figures 1-8 The method shown, and Figure 9 To achieve the above objectives, this application also provides a physical device for assessing cable health status, as illustrated in the virtual device embodiment. Specifically, this device can be a computer, smartphone, tablet, smartwatch, server, or network device, etc. The physical device includes a storage medium and a processor; the storage medium stores a computer program; the processor executes the computer program to achieve the above-described objectives. Figures 1-8 The method for assessing the health status of cables is shown.

[0087] Optionally, the physical device may also include a user interface, a network interface, a camera, radio frequency (RF) circuitry, sensors, audio circuitry, a Wi-Fi module, etc. The user interface may include a display screen, input units such as a keyboard, etc., and optional user interfaces may also include USB interfaces, card reader interfaces, etc. The network interface may optionally include standard wired interfaces, wireless interfaces (such as Wi-Fi interfaces), etc.

[0088] In an exemplary embodiment, see Figure 10 The aforementioned physical device includes a communication bus, a processor, a memory, and a communication interface. It may also include an input / output interface and a display device. The various functional units can communicate with each other via the bus. The memory stores a computer program, and the processor executes the program stored in the memory to perform the cable health status assessment method described in the above embodiments.

[0089] Those skilled in the art will understand that the physical device structure for assessing cable health status provided in this embodiment does not constitute a limitation on the physical device, and may include more or fewer components, or combine certain components, or have different component arrangements.

[0090] The storage medium may also include an operating system and a network communication module. The operating system is a program that manages the hardware and software resources of the physical device for assessing the cable health status, supporting the operation of information processing programs and other software and / or programs. The network communication module is used to enable communication between the various components within the storage medium, as well as communication with other hardware and software in the information processing physical device.

[0091] Through the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented using software plus necessary general-purpose hardware platforms, or it can be implemented through hardware. By applying the technical solution of this application, compared with the existing methods, this application realizes the full-element mapping of the physical entity of the cable in the information space through the cable, so that the static attributes and dynamic operating status of the physical entity of the cable can be accurately reproduced in the virtual information space; combined with the multi-dimensional index data of the cable collected by the digital perception layer, the matter-element extension model is driven to realize the multi-dimensional index evaluation of the cable health status, which greatly improves the accuracy of the cable health status evaluation results. It can not only accurately identify the type and location of the fault that has occurred, but also predict the potential deterioration trend of the cable, providing a basis for the refined operation and maintenance of the cable.

[0092] Those skilled in the art will understand that the accompanying drawings are merely schematic diagrams of a preferred embodiment, and the modules or processes shown in the drawings are not necessarily essential for implementing this application. Those skilled in the art will understand that the modules in the apparatus of the embodiment can be distributed within the apparatus of the embodiment as described, or can be modified to be located in one or more apparatuses different from this embodiment. The modules of the above-described embodiment can be combined into one module, or further divided into multiple sub-modules.

[0093] The serial numbers in this application are for descriptive purposes only and do not represent the superiority or inferiority of any particular implementation scenario. The above disclosures are merely a few specific implementation scenarios of this application; however, this application is not limited thereto, and any variations conceived by those skilled in the art should fall within the protection scope of this application.

Claims

1. A method of assessing the health of a cable, characterized by, The method comprises the following steps: pre-constructing a cable digital twin, which is a full-element holographic mapping of a cable physical entity in a digital virtual space; using a digital perception layer configured by the cable digital twin to establish information interaction between the cable physical entity and a sensor agent to obtain cable multi-dimensional index data of the cable physical entity; calling a matter-element extension model in a digital calculation layer configured by the cable digital twin to input the cable multi-dimensional index data into the matter-element extension model for health status evaluation and output evaluation results of the cable health status.

2. The method of claim 1, wherein, The digital perception layer comprises an external digital link and an internal digital link; after the pre-constructed cable digital twin, the method further comprises: using the external digital link to interface the sensor agent to collect multi-dimensional index original data of the cable physical entity through the sensor agent, and sending the multi-dimensional index original data to the internal digital link after standardization processing; using the internal digital link to distribute the standardized data uploaded by the external digital link to the digital calculation layer to establish a collaborative triggering mechanism between the internal functional modules of the digital twin.

3. The method of claim 1, wherein, The cable digital twin is configured with a digital twin layer; after the pre-constructed cable digital twin, the method further comprises: using the digital twin layer to construct a visual three-dimensional model consistent with the cable physical entity based on cable constituent data obtained by video acquisition technology, the visual three-dimensional model depicting the appearance, component composition and connection relationship between components of the cable physical entity, and the visual three-dimensional model containing a virtual mapping unit of a core component of the cable physical entity.

4. The method of claim 1, wherein, The cable digital twin is configured with a digital modeling layer, which is built-in a dual-protocol interaction interface and is provided with a first communication interaction unit and a second communication interaction unit; The first communication interaction unit uses a first communication standard to establish a bidirectional information interaction channel between the cable digital twin and the cable physical entity; After the pre-constructed cable digital twin, the method further comprises: using the first communication interaction unit of the digital modeling layer to transmit multi-dimensional operation index data of the cable physical entity to the digital twin and transmit control instructions of the cable digital twin to the cable physical entity; The second communication interaction unit uses a second communication standard to establish an information interaction channel between the cable digital twin and an external host system; after the pre-constructed cable digital twin, the method further comprises: using the second communication interaction unit of the digital modeling layer to transmit the evaluation results of the cable health status and the operation state data generated by the cable digital twin to the external host system, and transmit the scheduling instructions issued by the external host system to the cable digital twin.

5. The method of claim 4, wherein, The digital modeling layer further comprises a data analysis unit; after the pre-constructed cable digital twin, the method further comprises: A data analysis unit of the digital modeling layer performs protocol analysis on the heterogeneous information transmitted by the first communication interaction unit and the second communication interaction unit respectively, and uniformly converts the heterogeneous information into a standard common information model object and attribute format; The digital modeling layer further includes a message definition unit, and after the pre-constructed cable digital twin, the method further includes: A message definition unit of the digital modeling layer defines a standard common information model message, so that information exchange between the cable digital twin and an external host system is performed through the standard common information model message, and the standard common information model message at least includes a request message, a response message, an event message, and an error message; The digital modeling layer further includes a model extension unit, and after the pre-constructed cable digital twin, the method further includes: A model extension unit of the digital modeling layer performs customized extension modeling based on the standard common information model; specifically, based on the standard common information model, a cable exclusive entity class is added, and the exclusive entity class includes attribute parameters of a cable core component and a definition of a correlation between components, and the attribute parameters at least include material parameters, geometric size parameters, electrical performance parameters, and operating state parameters of the cable component.

6. The method according to any one of claims 1-5, characterized in that, The digital computing layer subscribes to cable multi-dimensional index data of a cable physical entity from a database of the digital modeling layer: Correspondingly, the cable multi-dimensional index data is input into the matter-element extension model for health state evaluation, and an evaluation result of the cable health state is output, including: Each cable dimension index is pre-divided into a plurality of health state levels, each health state level corresponds to a classical field, and the union set of all classical fields corresponds to a section field of the cable dimension index; An association function is used to calculate the association degree of the cable dimension index in the multi-cable dimension index data belonging to different health state levels; According to the association degree of the cable dimension index belonging to different health state levels, the evaluation result of the cable health state is determined.

7. The method of claim 6, wherein, According to the association degree of the cable dimension index belonging to different health state levels, the evaluation result of the cable health state is determined. According to the association degree of the cable dimension index belonging to different health state levels, the evaluation result of the cable health state is determined. According to the association degree of the cable dimension index belonging to different health state levels, the evaluation result of the cable health state is determined. According to the association degree of the cable dimension index belonging to different health state levels, the evaluation result of the cable health state is determined. According to the association degree of the cable dimension index belonging to different health state levels, the evaluation result of the cable health state is determined.

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According to A construction module is configured to pre-construct a cable digital twin, which is a full-element holographic mapping of a cable physical entity in a digital virtual space; An acquisition module is configured to establish information interaction between the cable physical entity and a sensor intelligent agent using a digital perception layer configured by the cable digital twin, so as to acquire cable multi-dimensional index data of the cable physical entity; An evaluation module is configured to call a matter-element extension model in a digital calculation layer configured by the cable digital twin, input the cable multi-dimensional index data into the matter-element extension model for health state evaluation, and output an evaluation result of the cable health state. 9.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-8 when the computer program is executed by the processor. The processor executes the computer program to implement the steps of the cable health state evaluation method in any one of claims 1 to 7.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the cable health state evaluation method in any one of claims 1 to 7.

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