Optical cable wiring activity display method and device based on digital twin technology

Abstract

The application discloses a kind of cable wiring activity display method and device based on digital twinborn technology, it is related to cable wiring operation and maintenance technical field, the specific steps of the method are: twinborn modeling, data acquisition, data processing, dynamic display and fault early warning;The application builds the digital twinborn model corresponding to physical cable wiring unit by laser three-dimensional point cloud scanning technology, gives only digital identity mark for each node of digital twinborn model, and simultaneously configures exclusive sensor code for acquisition device, binds the loss data, environmental data and sensor code, acquisition time stamp obtained by acquisition, establishes the mapping relationship of data and model node by characteristic quantization extraction and matching degree calculation, realizes the accurate and unique association of acquisition data and digital twinborn model node, so that various data of cable wiring can be accurately loaded to model corresponding node according to time dimension, complete the visual dynamic display of cable wiring loss data.

Description

Technical Field

[0001] This invention relates to the field of optical cable distribution maintenance technology, specifically to a method and device for displaying optical cable distribution activities based on digital twin technology. Background Technology

[0002] Optical fiber distribution is a core component of communication network transmission systems, widely used in the construction and daily operation and maintenance of various communication infrastructures such as communication equipment rooms, communication base stations, and fiber optic distribution frames. As communication networks develop towards higher speeds, larger scales, and greater density, the number of optical fiber distribution units deployed continues to increase, and the complexity of their layout also increases significantly. Their operating status directly affects the continuity and stability of communication signal transmission, and the industry's demand for status monitoring, visualization, and fault handling of optical fiber distribution units is becoming increasingly urgent.

[0003] However, existing fiber optic cable distribution-related display and monitoring technologies lack deep integration with digital twin models. There is no precise correlation logic between the collected data and the nodes of the digital twin model. No unique identifiers are configured for the acquisition devices and model nodes, and the collected data is not bound to the acquisition timestamp, making it impossible to distinguish the loss data of the same acquisition device at different times. At the same time, the collected data is only processed in a simple way, without eliminating the coupling effect of temperature and humidity on the loss data. Fault warnings rely solely on fixed thresholds and lack a mechanism for judging sudden changes in loss. Fault node location lacks precise basis, and the pushed information does not have targeted fault troubleshooting suggestions.

[0004] Therefore, a method and device for displaying optical cable wiring activities based on digital twin technology were developed. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a method and device for displaying optical cable distribution activities based on digital twin technology. This invention constructs a digital twin model corresponding to the physical optical cable distribution unit through laser three-dimensional point cloud scanning technology, assigns a unique digital identity to each node of the digital twin model, and configures dedicated sensor codes for the acquisition devices. The acquired loss data, environmental data, sensor codes, and acquisition timestamps are bound together. Through feature quantization extraction and matching degree calculation, a mapping relationship between data and model nodes is established, realizing a precise and unique association between the acquired data and the nodes of the digital twin model. This allows various types of data of optical cable distribution to be accurately loaded into the corresponding nodes of the model according to the time dimension, completing the visual and dynamic display of optical cable distribution loss data.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: On one hand, a method for displaying optical cable wiring activities based on digital twin technology, the specific steps of which are as follows:

[0007] Twin modeling: Using laser 3D point cloud scanning technology, based on the actual structure, size and wiring connection relationship of the physical optical cable wiring unit, the physical location of each joint, port and fusion splice in the physical optical cable wiring unit, as well as the interrelationship between the components, are restored to build a digital twin model of the optical cable wiring.

[0008] Data Acquisition: By deploying miniature fiber optic sensors and temperature and humidity acquisition components, real-time loss data and environmental correlation data of the physical optical cable distribution unit are collected and fused to form multi-source acquired data for transmission.

[0009] Data processing: Receive multi-source collected data, perform noise reduction processing, then perform environmental coupling correction to obtain noise-reduced effective data, and store the noise-reduced effective data;

[0010] Dynamic display: The noise-reduced effective data is transmitted to the digital twin model, and a mapping relationship is established between the noise-reduced effective data and each connector, port, and fusion splice node in the digital twin model. Different colors are used to indicate different loss levels, and the changing trend of real-time loss data in the noise-reduced effective data is displayed through dynamic waveforms.

[0011] Fault warning: Obtain real-time loss data from the effective data after noise reduction, set multi-level warning thresholds for fiber attenuation and connector loss, compare the real-time loss data from the effective data after noise reduction with the multi-level warning thresholds in real time, and locate the corresponding fault node in the digital twin model when the multi-level warning thresholds are exceeded, trigger the audible and visual warning unit to issue a fault warning, and push the fault node information and fault troubleshooting suggestions to the operation and maintenance terminal.

[0012] Furthermore, in the twin modeling process, laser 3D point cloud scanning technology is used to perform a full-dimensional scan of the physical optical cable distribution unit, obtaining the point cloud 3D structural data of the physical optical cable distribution unit. Point cloud deduplication and smoothing are then performed to extract the spatial coordinate parameters and fiber optic link connection parameters of each connector, port, and splice. These parameters are then imported into the digital twin modeling platform, and a geometric model of the physical optical cable distribution unit and a logical model of the fiber optic link are constructed at a 1:1 scale. These models are then fused to generate an initial digital twin model of the optical cable distribution unit. The spatial coordinate parameters and fiber optic link connection parameters of the initial digital twin model are then calibrated to complete the construction of the digital twin model of the optical cable distribution unit. Each connector, port, and splice node in the digital twin model is assigned a unique digital identity identifier, which includes the cabinet code, area code, and component code of the physical optical cable distribution unit. A node data interaction interface is then configured, binding the digital identity identifier to the node data interaction interface. Finally, the digital identity identifier is etched and bound to the physical identifier of the corresponding connector, port, or splice in the physical optical cable distribution unit.

[0013] Furthermore, in the data acquisition process, the miniature fiber optic sensor and the connectors, ports, and splices of the physical optical cable distribution unit are coupled using fiber optic fusion splicing. The temperature and humidity acquisition components are distributed and installed inside the cabinet of the physical optical cable distribution unit and in the surrounding environment outside the cabinet. The miniature fiber optic sensor collects real-time loss data of fiber attenuation and connector loss, while the temperature and humidity acquisition components collect environmental correlation data of ambient temperature and humidity in real time. Each miniature fiber optic sensor and temperature and humidity acquisition component is equipped with a unique sensor code, which includes the deployment location information of the acquisition device and the node information of the corresponding physical optical cable distribution unit. The collected fiber attenuation, connector loss, ambient temperature, and humidity data are bound with the sensor code and the acquisition timestamp, and then time-series fusion is performed to form multi-source acquisition data with acquisition timestamp and sensor code.

[0014] Furthermore, in the data processing, after denoising the multi-source acquired data, environmental coupling correction is performed on the real-time loss data based on environmental correlation data to eliminate the coupling influence of environmental temperature and humidity on fiber attenuation and connector loss. The corrected real-time loss data and environmental correlation data together constitute the denoised effective data. Each physical optical cable distribution unit is equipped with an independent loss data processing unit. The loss data processing unit classifies the denoised effective data according to the corresponding node and stores it in time sequence. An independent time-series database is established for each connector, port, and fusion splice node through the node digital identity identifier of the digital twin model. The denoised effective data is written into the time-series database of the corresponding node in the order of acquisition timestamp. The time-series database is configured with data read and write permissions and interacts with the digital twin model only through the node data interaction interface.

[0015] Furthermore, in the dynamic display, when establishing the mapping relationship between the denoised effective data and each node of the digital twin model, the sensor code, acquisition timestamp, and node digital identity associated with the sensor code are extracted through the node data interaction interface. Feature quantization is performed on both the sensor code and the node digital identity to obtain corresponding multi-dimensional feature values. The feature similarity between the sensor code feature value and the node digital identity feature value is calculated using the data-model node matching degree formula. This represents the matching degree between the denoised effective data acquired at the acquisition timestamp and the node of the digital twin model. When the matching degree is ≥0.9, the denoised valid data with the collection timestamp is associated with the corresponding node of the digital twin model. When the matching degree is <0.9, the sensor code feature value is re-extracted and the new matching degree is recalculated. When the new matching degree is ≥0.9, the association is performed directly. When the new matching degree is still <0.9, a sensor code-model node association anomaly alarm is generated and pushed to the operation and maintenance terminal. All associated denoised valid data are loaded into the node data display unit of the digital twin model in real time according to the collection timestamp order, completing the mapping of denoised valid data with each connector, port, and fusion splice node in the digital twin model.

[0016] Furthermore, in the dynamic display, the formula for the data-model node matching degree is: ,in, To determine the matching degree between the noise-reduced effective data and the nodes of the digital twin model, The first coded sensor 3D eigenvalues The first digital identity identifier for nodes in a digital twin model 3D eigenvalues is the dimension of the feature values.

[0017] Furthermore, in the fault early warning system, basic thresholds for fiber attenuation and connector loss are set based on the fiber link type and historical time-series statistical results of loss data of the optical cable distribution unit. These basic thresholds are then dynamically corrected using a multi-level early warning threshold dynamic correction formula, resulting in multi-level early warning thresholds for each level. Simultaneously, multiple sets of real-time loss data under the same sensor code are continuously monitored in time series. A loss mutation judgment formula is used to determine whether a sudden change occurs in the real-time loss data at adjacent acquisition timestamps. Fault early warning is triggered when the real-time loss data exceeds the multi-level early warning threshold or undergoes a sudden change. Fault node location is achieved through the association between sensor code and node digital identity. The pushed fault node information includes the node digital identity of the digital twin model, the cabinet code and area location of the physical optical cable distribution unit, the specific value of the real-time loss data corresponding to the fault acquisition timestamp, and the loss data mutation rate. The fault acquisition timestamp is the acquisition timestamp corresponding to the moment the fault occurred. Fault troubleshooting suggestions include fiber link inspection items corresponding to the loss fault type, component testing operation procedures, and fault repair process requirements. Fault node information and fault troubleshooting suggestions are pushed to the maintenance terminal in the form of text and data charts.

[0018] Furthermore, in the fault early warning system, the dynamic correction formula for the multi-level early warning threshold is as follows: ,in, Multi-level early warning thresholds, Based on the threshold, The correction factor was determined through analysis of the actual operation and maintenance requirements of the optical cable distribution unit and the link stability characteristics of data transmission. The degree of matching between the effective data after noise reduction and the nodes of the digital twin model.

[0019] Furthermore, in the fault warning, the formula for determining sudden loss is: ,in, For the loss data mutation rate, when When this occurs, it is determined that a sudden change has occurred in the real-time loss data; when At that time, it was determined that the real-time loss data had not changed abruptly. This is the real-time loss data at the current collection timestamp. This is the real-time loss data for the previous adjacent collection timestamp.

[0020] On the other hand, a fiber optic cable wiring demonstration device based on digital twin technology includes:

[0021] Twin Modeling Module: Using laser 3D point cloud scanning technology, based on the actual structure, size and wiring connection relationship of the physical optical cable wiring unit, the physical location of each joint, port and splice in the physical optical cable wiring unit, as well as the interrelationship between the components, are restored to build a digital twin model of the optical cable wiring.

[0022] Data acquisition module: By deploying miniature fiber optic sensors and temperature and humidity acquisition components, it collects real-time loss data and environmental correlation data of the physical optical cable distribution unit, and then merges them to form multi-source acquired data for transmission.

[0023] Data processing module: Receives multi-source collected data, performs noise reduction processing, performs environmental coupling correction, obtains noise-reduced effective data, and stores the noise-reduced effective data;

[0024] Dynamic display module: Transmits the noise-reduced effective data to the digital twin model, establishes a mapping relationship between the noise-reduced effective data and each connector, port, and fusion splice node in the digital twin model, identifies different loss levels with different colors, and displays the changing trend of real-time loss data in the noise-reduced effective data through dynamic waveforms.

[0025] Fault early warning module: It acquires real-time loss data from the effective data after noise reduction, sets multi-level early warning thresholds for fiber attenuation and connector loss, compares the real-time loss data from the effective data after noise reduction with the multi-level early warning thresholds in real time, and locates the corresponding fault node in the digital twin model when the multi-level early warning thresholds are exceeded, triggers the audible and visual early warning unit to issue a fault warning, and pushes fault node information and fault troubleshooting suggestions to the operation and maintenance terminal.

[0026] Compared with existing technologies, this method and device for demonstrating optical cable wiring based on digital twin technology has the following advantages:

[0027] I. This invention constructs a digital twin model corresponding to the physical optical cable distribution unit using laser 3D point cloud scanning technology. Each node of the digital twin model is assigned a unique digital identity, and dedicated sensor codes are configured for the acquisition devices. The acquired loss data, environmental data, sensor codes, and acquisition timestamps are bound together. Through feature quantization extraction and matching degree calculation, a mapping relationship between data and model nodes is established, achieving a precise and unique association between the acquired data and the digital twin model nodes. This allows various types of data from the optical cable distribution to be accurately loaded into the corresponding nodes of the model according to the time dimension, completing the visual and dynamic display of optical cable distribution loss data.

[0028] Second, this invention performs noise reduction processing on multi-source acquired data, and combines the acquired environmental correlation data to carry out environmental coupling correction on real-time loss data, eliminating the natural influence of environmental temperature and humidity on loss data. Then, it dynamically corrects the basic threshold of fault warning by combining the matching degree between data and model nodes. At the same time, it continuously monitors multiple sets of real-time loss data under the same sensor code and determines whether the loss data has changed abruptly. Through the association relationship between sensor code and digital identity of model node, it achieves accurate location of fault nodes, triggers the audible and visual warning unit to issue a fault warning, and pushes fault content containing node information, loss data and troubleshooting suggestions to the operation and maintenance terminal. This makes the judgment logic of fault warning fit the actual operating status of optical cable distribution, and achieves accurate location of fault nodes and accurate push of warning information.

[0029] Other advantages, objectives and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination or study, or may be learned from the practice of the invention. Attached Figure Description

[0030] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0031] Figure 1 A flowchart illustrating a method for demonstrating optical cable wiring activities based on digital twin technology;

[0032] Figure 2 This is a framework diagram of a fiber optic cable wiring demonstration device based on digital twin technology.

[0033] Figure 3 This is a framework diagram of a fault early warning system in a fiber optic cable wiring activity demonstration method based on digital twin technology. Detailed Implementation

[0034] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0035] Example:

[0036] In the operation and maintenance scenario of optical cable distribution cabinets in urban core communication equipment rooms, the urban core communication equipment room serves as the core hub of the regional communication network. Various communication transmission and switching equipment are densely arranged in an array. The 24-core optical cable distribution cabinets in the core transmission area connect to multi-link optical fiber signals. The optical fiber connectors, ports, and splices integrated in the cabinet are key nodes for signal transmission, directly supporting the massive data interaction and transmission of 5G core network and metropolitan area network. The equipment room is equipped with a precision constant temperature and humidity control unit to stabilize the ambient temperature within a suitable range for the operation of communication equipment and maintain the humidity within a low fluctuation range to ensure the basic operating environment of the equipment. However, due to the frequent daily operation and maintenance of the equipment room, including optical fiber patch cord adjustment, equipment inspection, port maintenance, etc., the optical fiber connection parts of the optical cable distribution cabinet are easily disturbed, causing problems such as loose connectors and micro-bending of optical fibers, which in turn leads to abnormal optical fiber loss.

[0037] For the 24-core optical fiber distribution cabinet in the core transmission area of ​​the data center, laser 3D point cloud scanning technology was used to conduct a full-dimensional, high-resolution scan. The scanning process covered the overall structure of the cabinet, all internal connection nodes, and the fiber optic link routing, completing the comprehensive acquisition of point cloud 3D structural data. The collected point cloud data underwent deduplication and smoothing to remove invalid noise points caused by equipment reflections and spatial electromagnetic interference within the data center. The spatial coordinate parameters of each connector, port, and splice within the cabinet, as well as the fiber optic link connection parameters between each node, were accurately extracted. These extracted parameters were imported into a digital twin modeling platform, and a physical geometric model of the optical fiber distribution cabinet and a logical topology model of the fiber optic links were accurately constructed at a 1:1 scale, fusing them to generate an initial digital twin model of the optical fiber distribution. Based on the actual deployment coordinates of the data center cabinet array, the spatial coordinate parameters and fiber optic link connection parameters of the initial digital twin model of the optical fiber distribution were calibrated point by point to ensure that the node positions and link routing of the initial digital twin model of the optical fiber distribution were completely matched with those of the physical cabinet, thus completing the construction of the digital twin model of the optical fiber distribution. Figure 1 As shown, each connector, port, and splice node in the digital twin model is assigned a unique digital identity, including cabinet code, equipment room area code, and component unique code. At the same time, a dedicated node data interaction interface is configured for the digital twin model, and each digital identity is bound to the node data interaction interface. On the metal components of each connector, port, and splice in the physical optical cable distribution cabinet, a digital identity that is completely consistent with the model node is engraved using laser etching technology, completing the etching binding between the physical end and the digital end, and realizing the unique correspondence between the physical node and the digital node.

[0038] Miniature fiber optic sensors are integrated into all connectors, ports, and splices of this 24-core fiber optic distribution cabinet. These sensors are coupled to each physical connection node using fiber optic fusion splices, ensuring a high degree of accuracy between the collected data and the actual fiber loss. Simultaneously, high-sensitivity temperature and humidity acquisition components are distributed throughout the cabinet's interior corners and surrounding areas to accurately collect temperature and humidity data, enabling simultaneous acquisition of real-time loss data and environmental correlation data. Each miniature fiber optic sensor and temperature / humidity acquisition component is assigned a unique sensor code containing the device's specific location and the node information of the corresponding physical fiber optic distribution unit, permanently binding the acquisition device to the sensor code. The miniature fiber optic sensors and temperature / humidity acquisition components collect real-time loss data (fiber attenuation, connector loss) and environmental correlation data (temperature and humidity). Each collected data set is bound to its own sensor code and the timestamp of the current acquisition. All bound data are then fused sequentially to form multi-source acquired data with timestamps and sensor codes, which is then transmitted. Figure 2 As shown.

[0039] The system receives and transmits multi-source data, performs noise reduction processing, and removes invalid data caused by electromagnetic interference in the equipment room and minor errors in the sensors themselves, resulting in noise-reduced multi-source data. Based on environmental correlation data in the noise-reduced multi-source data, environmental coupling correction is applied to the real-time loss data to eliminate the coupling effect of minor fluctuations in temperature and humidity in the equipment room on fiber optic attenuation and connector loss, ensuring that the loss data accurately reflects the actual operating status of the fiber optic link. The corrected real-time loss data and environmental correlation data together constitute the effective data after noise reduction. This physical optical cable distribution cabinet is equipped with a separate independent loss data processing unit and is deployed in the equipment room. The edge computing rack and loss data processing unit classify the noise-reduced effective data according to the corresponding nodes and store it in time series. Through the digital identity identifier of the nodes in the digital twin model, an independent time series database is established for each connector, port, and fusion splice node in the cabinet. The noise-reduced effective data is written into the time series database of the corresponding node in the order of collection timestamps, and each time series database is configured with exclusive hierarchical data read and write permissions. Directional data interaction with the optical cable distribution digital twin model is only allowed through the preset node data interaction interface, ensuring the security and uniqueness of data transmission.

[0040] The denoised effective data is transmitted via high-speed industrial Ethernet in the data center to the digital twin model of the fiber optic cabling. The digital twin model connects to the visualization screen and maintenance terminal of the data center monitoring center to achieve multi-terminal synchronous display of data. When establishing the mapping relationship between the denoised effective data and each node of the digital twin model, the sensor code, acquisition timestamp, and the node digital identity identifier pre-associated with the sensor code are first extracted from the denoised effective data through the node data interaction interface. Feature quantization is then performed on the sensor code and the node digital identity identifier to obtain their respective multi-dimensional feature values. The feature similarity between the sensor code feature value and the node digital identity identifier feature value is then calculated using the data-model node matching degree formula. This similarity is the matching degree between the denoised effective data acquired by the corresponding sensor code at that acquisition timestamp and the node of the digital twin model. The data-model node matching degree formula is as follows: ,in, To determine the matching degree between the noise-reduced effective data and the nodes of the digital twin model, The first coded sensor 3D eigenvalues The first digital identity identifier for nodes in a digital twin model 3D eigenvalues The dimension of the feature value is used. When the matching degree is ≥0.9, the denoised valid data of the strip's acquisition timestamp is directly associated with the corresponding node of the digital twin model. When the matching degree is <0.9, the sensor code feature value is re-extracted and the new matching degree is recalculated. When the new matching degree is ≥0.9, the association between the data and the node is completed directly. When the new matching degree is still <0.9, an alarm for sensor code-model node association is immediately generated and the alarm information is pushed to the data center monitoring console and operation and maintenance terminal. After all data is associated with the nodes of the digital twin model, the associated denoised valid data is loaded into the node data display unit of the digital twin model in real time according to the acquisition timestamp order. Different loss levels are clearly marked on the visualization screen with different colors. The continuous change trend of real-time loss data in the denoised valid data is displayed in real time through dynamic waveform curves. Finally, the accurate mapping between the denoised valid data and the nodes of each connector, port, and fusion joint of the digital twin model is completed.

[0041] Real-time loss data from the noise-reduced effective data is obtained through the node data interaction interface. Based on the fiber optic link type, transmission bandwidth requirements, and time-series statistical results of historical loss data for the optical cable distribution cabinet, basic thresholds for fiber attenuation and connector loss are set. Combined with the data-model node matching degree, the basic thresholds are dynamically corrected in real-time using a multi-level early warning threshold dynamic correction formula. This yields multi-level early warning thresholds that align with the actual reliability of the data. The multi-level early warning threshold dynamic correction formula is as follows: ,in, Multi-level early warning thresholds, Based on the threshold, The correction factor was determined through analysis of the actual operation and maintenance requirements of the optical cable distribution unit and the link stability characteristics of data transmission. To determine the matching degree between the effective data after noise reduction and the nodes of the digital twin model; simultaneously, to continuously monitor multiple sets of real-time loss data under the same sensor encoding, and to continuously determine whether a sudden change occurs in the real-time loss data at adjacent acquisition timestamps using a loss mutation determination formula, the loss mutation determination formula is as follows: ,in, For the loss data mutation rate, when When this occurs, it is determined that a sudden change has occurred in the real-time loss data; when At that time, it was determined that the real-time loss data had not changed abruptly, with 0.1 being the threshold for determining a change in data. This threshold was determined based on statistical analysis of historical operational data throughout the entire lifecycle of the optical cable distribution unit. This is the real-time loss data at the current collection timestamp. This provides real-time loss data from the previous adjacent acquisition timestamp. When the real-time loss data exceeds the multi-level warning threshold or is determined to have undergone a sudden change, a fault warning is immediately triggered. Through the unique association between sensor coding and node digital identity, the fault node is accurately located, and its location is highlighted on the digital twin model. Simultaneously, an audible and visual warning unit installed next to the optical cable distribution cabinet is triggered, issuing a fault warning signal. The fault node information and troubleshooting suggestions are then pushed to the maintenance terminal. Figure 3 As shown, the fault node information includes the node's digital identity in the digital twin model, the cabinet code of the physical optical cable distribution unit and its specific location in the computer room, the specific value of the real-time loss data corresponding to the fault collection timestamp, and the loss data mutation rate. The fault troubleshooting suggestions include professional inspection items for the optical fiber link corresponding to the type of loss fault, standardized component testing procedures in the computer room, and fault repair process requirements adapted to the core computer room equipment. Furthermore, the fault node information and troubleshooting suggestions are presented intuitively in the form of text and data charts, adapting to the operational needs of professional computer room operation and maintenance.

[0042] In summary, by building a digital twin model that matches the physical optical cable distribution cabinet, the precise binding of physical and digital nodes is achieved. Then, through multi-dimensional data collection and processing, a precise mapping between the collected data and model nodes is established, enabling dynamic display of optical cable distribution loss data. At the same time, combined with dynamically corrected early warning thresholds and loss mutation judgment, fault early warning is achieved, fault nodes are accurately located, and targeted troubleshooting suggestions are pushed. This meets the high-requirement operation and maintenance needs of core data centers and solves the problems of slow response and ambiguous positioning in traditional operation and maintenance models.

[0043] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A method for demonstrating optical cable wiring activities based on digital twin technology, characterized in that, The specific steps of this method are as follows: Twin modeling: Using laser 3D point cloud scanning technology, based on the actual structure, size and wiring connection relationship of the physical optical cable wiring unit, the physical location of each joint, port and splice in the physical optical cable wiring unit, as well as the interrelationship between the components, are restored to build a digital twin model of the optical cable wiring. Data acquisition: By deploying miniature fiber optic sensors and temperature and humidity acquisition components, real-time loss data and environmental correlation data of physical optical cable distribution units are collected in real time, and then fused to form multi-source acquired data for transmission. Data processing: Receive multi-source collected data, perform noise reduction processing, then perform environmental coupling correction to obtain noise-reduced effective data, and store the noise-reduced effective data; Dynamic display: The noise-reduced effective data is transmitted to the digital twin model, and a mapping relationship is established between the noise-reduced effective data and each connector, port, and fusion splice node in the digital twin model. Different colors are used to indicate different loss levels, and the changing trend of real-time loss data in the noise-reduced effective data is displayed through dynamic waveforms. Fault warning: Obtain real-time loss data from the effective data after noise reduction, set multi-level warning thresholds for fiber attenuation and connector loss, compare the real-time loss data from the effective data after noise reduction with the multi-level warning thresholds in real time, and locate the corresponding fault node in the digital twin model when the multi-level warning thresholds are exceeded, trigger the audible and visual warning unit to issue a fault warning, and push the fault node information and fault troubleshooting suggestions to the operation and maintenance terminal.

2. The method for displaying optical cable wiring activities based on digital twin technology according to claim 1, characterized in that, In the digital twin modeling process, laser 3D point cloud scanning technology is used to perform a full-dimensional scan of the physical optical cable distribution unit, acquiring the 3D point cloud structure data of the physical optical cable distribution unit. Point cloud deduplication and smoothing are then performed to extract the spatial coordinate parameters and fiber optic link connection parameters of each connector, port, and splice. These parameters are then imported into the digital twin modeling platform, where a geometric model of the physical optical cable distribution unit and a logical model of the fiber optic link are constructed at a 1:1 scale. These models are then fused to generate an initial digital twin model of the optical cable distribution unit. The spatial coordinate parameters and fiber optic link connection parameters of the initial digital twin model are then calibrated to complete the construction of the digital twin model. Each connector, port, and splice node in the digital twin model is assigned a unique digital identity, which includes the cabinet code, area code, and component code of the physical optical cable distribution unit. A node data interaction interface is then configured, binding the digital identity to the node data interaction interface. Finally, the digital identity is etched and bound to the physical identifier of the corresponding connector, port, or splice in the physical optical cable distribution unit.

3. The method for displaying optical cable wiring activities based on digital twin technology according to claim 1, characterized in that, In the data acquisition process, the miniature fiber optic sensors are coupled to the connectors, ports, and splices of the physical optical cable distribution unit using fiber optic fusion splicing. The temperature and humidity acquisition components are distributed and installed inside the cabinet of the physical optical cable distribution unit and in the surrounding environment outside the cabinet. The miniature fiber optic sensors collect real-time loss data of fiber attenuation and connector loss, while the temperature and humidity acquisition components collect real-time environmental correlation data of ambient temperature and humidity. Each miniature fiber optic sensor and temperature and humidity acquisition component is equipped with a unique sensor code, which includes the deployment location information of the acquisition device and the node information of the corresponding physical optical cable distribution unit. The collected fiber attenuation, connector loss, ambient temperature, and humidity data are bound with the sensor code and the acquisition timestamp, and then time-series fusion is performed to form multi-source acquired data with acquisition timestamps and sensor codes.

4. The method for displaying optical cable wiring activities based on digital twin technology according to claim 1, characterized in that, In the data processing, after noise reduction of multi-source acquired data, environmental coupling correction is performed on real-time loss data based on environmental correlation data to eliminate the coupling influence of environmental temperature and humidity on fiber attenuation and connector loss. The corrected real-time loss data and environmental correlation data together constitute the noise-reduced effective data. Each physical optical cable distribution unit is equipped with an independent loss data processing unit. The loss data processing unit classifies the noise-reduced effective data according to the corresponding node and stores it in time series. An independent time series database is established for each connector, port, and splice node through the node digital identity identifier of the digital twin model. The noise-reduced effective data is written into the time series database of the corresponding node in the order of acquisition timestamp. The time series database is configured with data read and write permissions and interacts with the digital twin model only through the node data interaction interface.

5. The method for displaying optical cable wiring activities based on digital twin technology according to claim 1, characterized in that, In the dynamic display, when establishing the mapping relationship between the denoised effective data and each node of the digital twin model, the sensor code, acquisition timestamp, and node digital identity associated with the sensor code are extracted through the node data interaction interface. Feature quantization is performed on the sensor code and node digital identity to obtain corresponding multi-dimensional feature values. The feature similarity between the sensor code feature value and the node digital identity feature value is calculated using the data-model node matching degree formula. This represents the matching degree between the denoised effective data acquired at the acquisition timestamp and the node of the digital twin model. When the matching degree is ≥0.9, the denoised valid data with the collection timestamp is associated with the corresponding node of the digital twin model. When the matching degree is <0.9, the sensor code feature value is re-extracted and the new matching degree is recalculated. When the new matching degree is ≥0.9, the association is performed directly. When the new matching degree is still <0.9, a sensor code-model node association anomaly alarm is generated and pushed to the operation and maintenance terminal. All associated denoised valid data are loaded into the node data display unit of the digital twin model in real time according to the collection timestamp order, completing the mapping of denoised valid data with each connector, port, and fusion splice node in the digital twin model.

6. The method for displaying optical cable wiring activities based on digital twin technology according to claim 5, characterized in that, In the dynamic display, the formula for the data-model node matching degree is: ,in, To determine the matching degree between the noise-reduced effective data and the nodes of the digital twin model, The first coded sensor 3D eigenvalues The first digital identity identifier for nodes in a digital twin model 3D eigenvalues is the dimension of the feature values.

7. The method for displaying optical cable wiring activities based on digital twin technology according to claim 1, characterized in that, In the fault early warning system, basic thresholds for fiber attenuation and connector loss are set based on the fiber link type and historical time-series statistical results of loss data of the optical cable distribution unit. These basic thresholds are then dynamically corrected using a multi-level early warning threshold dynamic correction formula, resulting in multi-level early warning thresholds for each level. Simultaneously, multiple sets of real-time loss data under the same sensor code are continuously monitored in time series. A loss mutation judgment formula is used to determine whether a sudden change occurs in the real-time loss data at adjacent acquisition timestamps. Fault early warning is triggered when the real-time loss data exceeds the multi-level early warning threshold or undergoes a sudden change. Fault node location is achieved through the association between sensor code and node digital identity. The pushed fault node information includes the node digital identity of the digital twin model, the cabinet code and area location of the physical optical cable distribution unit, the specific value of the real-time loss data corresponding to the fault acquisition timestamp, and the loss data mutation rate. Fault troubleshooting suggestions include fiber link inspection items corresponding to the loss fault type, component testing operation procedures, and fault repair process requirements. Fault node information and fault troubleshooting suggestions are pushed to the maintenance terminal in the form of text and data charts.

8. The method for displaying optical cable wiring activities based on digital twin technology according to claim 7, characterized in that, In the aforementioned fault early warning system, the dynamic correction formula for the multi-level early warning threshold is as follows: ,in, Multi-level early warning thresholds, Based on the threshold, The correction factor was determined through analysis of the actual operation and maintenance requirements of the optical cable distribution unit and the link stability characteristics of data transmission. The degree of matching between the effective data after noise reduction and the nodes of the digital twin model.

9. A method for displaying optical cable distribution activities based on digital twin technology according to claim 7, characterized in that, In the fault warning, the formula for determining sudden loss is: ,in, For the loss data mutation rate, when When this occurs, it is determined that a sudden change has occurred in the real-time loss data; when At that time, it was determined that the real-time loss data had not changed abruptly. This is the real-time loss data at the current collection timestamp. This is the real-time loss data for the previous adjacent collection timestamp.

10. A device for displaying optical cable wiring activities based on digital twin technology, the device being applicable to the method for displaying optical cable wiring activities based on digital twin technology as described in any one of claims 1-9, characterized in that, The device includes: Twin Modeling Module: Using laser 3D point cloud scanning technology, based on the actual structure, size and wiring connection relationship of the physical optical cable wiring unit, the physical location of each joint, port and splice in the physical optical cable wiring unit, as well as the interrelationship between the components, are restored to build a digital twin model of the optical cable wiring. Data acquisition module: By deploying miniature fiber optic sensors and temperature and humidity acquisition components, it collects real-time loss data and environmental correlation data of the physical optical cable distribution unit, and then merges them to form multi-source acquired data for transmission. Data processing module: Receives multi-source collected data, performs noise reduction processing, performs environmental coupling correction, obtains noise-reduced effective data, and stores the noise-reduced effective data; Dynamic display module: Transmits the noise-reduced effective data to the digital twin model, establishes a mapping relationship between the noise-reduced effective data and each connector, port, and fusion splice node in the digital twin model, identifies different loss levels with different colors, and displays the changing trend of real-time loss data in the noise-reduced effective data through dynamic waveforms. Fault early warning module: It acquires real-time loss data from the effective data after noise reduction, sets multi-level early warning thresholds for fiber attenuation and connector loss, compares the real-time loss data from the effective data after noise reduction with the multi-level early warning thresholds in real time, and locates the corresponding fault node in the digital twin model when the multi-level early warning thresholds are exceeded, triggers the audible and visual early warning unit to issue a fault warning, and pushes fault node information and fault troubleshooting suggestions to the operation and maintenance terminal.

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