CN120321103B - Dumb resource lifecycle management method and system supporting RFID automatic identification - Google Patents

Abstract

The application provides a dummy resource life cycle management method and system supporting RFID automatic identification, which relate to the technical field of dummy resource monitoring management and comprise the steps of performing relay identification link activation according to a dummy resource fault output by a dummy resource fault detection node, automatically identifying a node RFID corresponding to the dummy resource fault, and extracting equipment history information; the service life of the equipment is predicted and stored and updated according to the fault of the dummy resources and the historical information of the equipment, the dummy resource identification cloud end screens and positions the risk optical cable according to the uploading time stamp of the fault of the dummy resources and performs fault positioning, and the service life of the optical cable is predicted and stored and updated according to the fault positioning result. The application solves the technical problems that the service life of the dummy resources cannot be accurately predicted and the maintenance optimization capability is insufficient due to the fact that the historical operation and maintenance data are ignored only by considering the current fault condition in the prior art, and achieves the technical effects of improving the prediction accuracy of the service life of the dummy resources and further realizing the refined management of the dummy resources.

Description

Dumb resource lifecycle management method and system supporting RFID automatic identification

Technical Field

The present application relates to the technical field of dumb resource monitoring and management, and specifically to a dumb resource lifecycle management method and system supporting RFID automatic identification.

Background Art

In the communications and networking fields, dumb resources are those that cannot proactively provide operational status and fault information, such as pipes, poles, and optical cables in optical networks. Managing these resources is crucial to ensuring stable network operation and efficient maintenance.

Currently, the status monitoring and management of dumb resources primarily relies on periodic maintenance and passive fault repair. Periodic maintenance relies on inspection and replacement at fixed intervals, but lacks specificity and can lead to wasted resources or insufficient maintenance. Passive fault repair, on the other hand, only conducts troubleshooting and repairs after a fault occurs, which can easily lead to unexpected outages and long recovery times. Furthermore, while some advanced detection technologies (such as OTDR fiber testing) can provide certain status monitoring capabilities, they still rely primarily on single-point testing and lack global data fusion analysis, making it impossible to accurately predict the lifespan and potential failure risks of dumb resources.

Summary of the Invention

This application provides a dumb resource lifecycle management method and system that supports RFID automatic identification, which solves the technical problem that the existing technology only considers the current fault situation and ignores historical operation and maintenance data, resulting in the inability to accurately predict the dumb resource life and insufficient maintenance optimization capabilities. It achieves the technical effect of improving the accuracy of dumb resource life prediction and thus realizing refined management of dumb resources.

In view of the above problems, on the one hand, the present application provides a dumb resource lifecycle management method that supports RFID automatic identification, the method comprising: after the first dumb resource fault detection node analyzes and outputs the first dumb resource fault, activating the relay identification link according to the first dumb resource fault to automatically identify the first node RFID corresponding to the first dumb resource fault and extract the first device history information, wherein the RFID automatic identification is achieved by the coordinated work of a fixed RFID reader and a relay device; performing a life attenuation prediction based on the first dumb resource fault and the first device history information, outputting the first updated device life, and storing the first updated device life to the first node RFID; after receiving the first dumb resource fault, the dumb resource identification cloud performs associated risk optical cable screening according to the first upload timestamp of the first dumb resource fault and locates the first risk optical cable; after locating the fault according to the first optical cable troubleshooting vector identifier of the first risk optical cable, performing an optical cable life prediction based on the fault location result to output the first updated optical cable life of the first risk optical cable, and storing the first updated optical cable life in the first optical cable RFID of the first risk optical cable.

On the other hand, the present application also provides a dumb resource lifecycle management system that supports RFID automatic identification, the system including: a relay identification link activation module, which is used to activate the relay identification link according to the first dumb resource fault after the first dumb resource fault detection node analyzes and outputs the first dumb resource fault, so as to automatically identify the first node RFID corresponding to the first dumb resource fault and extract the first device history information, wherein the RFID automatic identification is achieved by the coordinated operation of a fixed RFID reader and a relay device; an equipment life prediction module, which is used to predict the life attenuation based on the first dumb resource fault and the first device history information, output the first updated equipment life, and store the first updated equipment life to the first node RFID; an associated risk optical cable screening module, which is used for the dumb resource identification cloud to screen associated risk optical cables according to the first upload timestamp of the first dumb resource fault after receiving the first dumb resource fault, and locate the first risk optical cable; an optical cable life prediction module, which is used to locate the fault based on the first optical cable troubleshooting vector identifier of the first risk optical cable, predict the optical cable life based on the fault location result, output the first updated optical cable life of the first risk optical cable, and store the first updated optical cable life in the first optical cable RFID of the first risk optical cable.

One or more technical solutions provided in this application have at least the following beneficial effects:

After the first dumb resource fault detection node analyzes and outputs the fault, it activates the relay identification link, enabling rapid response and precise location of the dumb resource fault. It also obtains historical O&M data for the faulty device, providing a foundation for subsequent lifespan prediction and maintenance strategy adjustments. Based on the fault and the extracted historical information, it performs a lifespan attenuation prediction, outputs an updated device lifespan, and stores it on the corresponding node's RFID. This step improves the accuracy of lifespan prediction by comprehensively analyzing historical and real-time data, outputting an updated device lifespan, and facilitating more efficient maintenance and upgrade planning. The updated device lifespan is stored on the first node's RFID, facilitating subsequent query and management while also enabling localized data storage. After receiving the fault, the dumb resource identification cloud identifies and locates associated risky optical cables based on the fault's upload timestamp, expanding its management scope from a single faulty node to encompass associated optical cables and other resources. Based on the fault location results, it predicts the optical cable lifespan, updates the cable lifespan, and stores it on the cable's RFID, facilitating management and monitoring.

In summary, this application has achieved rapid detection and location of dumb resource failures by introducing RFID automatic identification technology, combined with historical dumb resource operation and maintenance data and current fault conditions to predict lifespan, thereby improving the accuracy of lifespan prediction. Secondly, dumb resource failures are correlated with associated risk optical cables for analysis, achieving comprehensive management from dumb resources to optical cables and broadening the scope of management. This comprehensive management approach can dynamically update the predicted dumb resource lifespan, improve the efficiency and accuracy of fault handling, thereby significantly improving the management efficiency and resource utilization of dumb resources and achieving refined management of dumb resources.

The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a flow chart of a method for managing a lifecycle of a dumb resource supporting RFID automatic identification according to an embodiment of the present application.

FIG2 is a flow chart of obtaining a relay identification link in a dumb resource lifecycle management method supporting RFID automatic identification provided in an embodiment of the present application.

FIG3 is a schematic diagram of the structure of a dumb resource lifecycle management system supporting RFID automatic identification provided in an embodiment of the present application.

Description of reference numerals: relay identification link activation module 10 , equipment life prediction module 20 , associated risk optical cable screening module 30 , optical cable life prediction module 40 .

DETAILED DESCRIPTION

The embodiments of the present application provide a dumb resource lifecycle management method and system that supports RFID automatic identification, thereby solving the technical problems of the prior art that only considers current fault conditions and ignores historical operation and maintenance data, resulting in the inability to accurately predict the life of dumb resources and insufficient maintenance optimization capabilities. This achieves the technical effect of improving the accuracy of dumb resource life prediction and further realizing refined management of dumb resources.

In the first embodiment, as shown in FIG1 , the present application provides a method for managing a lifecycle of a dumb resource supporting RFID automatic identification, the method comprising:

Step S1: After the first dumb resource fault detection node analyzes and outputs the first dumb resource fault, the relay identification link is activated according to the first dumb resource fault to automatically identify the first node RFID corresponding to the first dumb resource fault and extract the first device history information, wherein the RFID automatic identification is achieved through the collaborative work of a fixed RFID reader and a relay device.

Specifically, dumb resources are those that cannot proactively provide operational status and fault information, such as pipes, poles, and optical cables in optical networks. A dumb resource fault detection node is a node in a dumb resource monitoring system responsible for detecting and outputting dumb resource fault information. It can be a monitoring terminal or a fault detection module integrated into the system. A relay identification link is a link used to activate and establish an RFID connection with the node corresponding to the fault after a dumb resource fault is detected. This link, composed of multiple relay devices and RFID nodes, facilitates automatic identification. Relay devices are used to extend and enhance the RFID system's read range, enabling efficient information transfer between RFID nodes.

The first dumb resource fault detection node uses its own detection capabilities (e.g., using sensors to detect abnormalities in equipment operating parameters) to analyze whether a first dumb resource fault has occurred. After analyzing and outputting the first dumb resource fault, the first dumb resource fault detection node triggers the activation of a relay identification link based on this fault information. The activated relay identification link connects to the first node RFID tag corresponding to the first dumb resource fault. This first node RFID tag stores relevant information about the device at that node, such as basic device information and historical operation and maintenance data. Radio waves emitted by a fixed RFID reader/writer are used to automatically identify and read the information stored in the node RFID tag, thereby extracting the first device's historical information. For example, in an optical communication network, if a fault detection node on a fiber optic cable segment detects a signal transmission anomaly and identifies it as a fiber optic cable fault, it activates the corresponding relay identification link, connects to the RFID tag corresponding to that fiber optic cable segment, and reads the stored historical information about the fiber optic cable segment, including past maintenance records and fault handling status.

After discovering a dumb resource failure, the link is activated to automatically identify the relevant node RFID, thereby obtaining the historical operation and maintenance data of the equipment. This provides basic data for subsequent operations such as life decay prediction, enabling the entire management process to make decisions based on more comprehensive information, thereby improving the accuracy of dumb resource management.

Step S2: Perform life attenuation prediction based on the first dummy resource failure and first device history information, output a first updated device life, and store the first updated device life to the first node RFID.

Specifically, after obtaining the first dumb resource fault and the first device's historical information, the service life prediction algorithm uses these two as input data to predict the remaining service life of the device, obtaining the estimated remaining service life after the device is updated, which is recorded as the first updated device life. This first updated device life reflects the expected service life of the device in its current state. In specific implementations, life prediction can be performed based on data mining and machine learning algorithms, such as regression algorithms in machine learning. This involves training a linear regression model using the device usage time and historical operating temperature data from the first device's historical information as independent variables and a device performance indicator (such as a quantitative value of the device's remaining service life) as the dependent variable. This training process can be performed using the linear regression module in the Python Scikit-learn library. The performance degradation caused by the current fault (e.g., a Y% decrease in a key performance indicator of the device) obtained from the first dumb resource fault information is input into the trained linear regression model to obtain the model's predicted remaining service life. For example, for an optical cable splice closure with multiple maintenance records and current fault information, this data can be input into a pre-trained linear regression model to predict a remaining service life of six months. Alternatively, a physics-based model can be used to establish a multi-factor model that considers factors such as the device's material properties and operating environment to predict lifespan. After obtaining the first updated device lifespan, this information is stored back to the first node's RFID reader via an RFID writer, ensuring timely access to the latest lifespan predictions during subsequent management and maintenance.

By combining current faults and historical information to predict life attenuation, the accuracy of equipment life prediction is improved, so that managers or management systems can plan equipment maintenance and updates more scientifically, thereby optimizing dumb resource management and improving resource utilization efficiency.

Step S3: Dumb Resource Identification After receiving the first dumb resource fault, the cloud performs associated risk optical cable screening based on the first upload timestamp of the first dumb resource fault to locate the first risk optical cable.

Specifically, the dumb resource identification cloud is a cloud computing platform responsible for receiving, processing, and analyzing dumb resource-related data, such as fault information and historical device data, to provide intelligent support for dumb resource management. The first upload timestamp is the time stamp when the first dumb resource fault information is uploaded to the dumb resource identification cloud. It is used to determine the specific time of fault occurrence and upload. The first risk optical cable is a screened and identified optical cable associated with the first dumb resource fault and potentially at risk. The first optical cable troubleshooting vector is a data vector used to identify the health status of the optical cable. It can include parameters such as the cable's location, number of historical faults, and signal attenuation, facilitating further fault location and analysis. For example, a troubleshooting vector might be (0.85, 2, 5), indicating that the optical cable health is 0.85 and that it has experienced five faults in the past two years.

When the dumb resource identification cloud receives the first dumb resource fault information, it obtains the timestamp of the fault information upload, i.e., the first upload timestamp. Then, using data mining and association analysis algorithms, combined with information in the optical cable database, it filters out the optical cables that may be associated with the fault from all the optical cable data based on the timestamp as the first risk optical cables, and identifies the first optical cable troubleshooting vector for them. For example, in a large communication network, the fault information of a certain optical cable segment A is uploaded to the cloud at 10 am. The cloud analyzes and finds that the signal attenuation of the branch optical cable B adjacent to the optical cable segment A increases during the same time period. In this case, the optical cable B is marked as the first risk optical cable, and the first optical cable troubleshooting vector containing its location, model, and other information is generated.

By screening associated risk optical cables based on upload timestamps, the management scope is expanded from a single fault node to associated optical cables and other resources. This helps to quickly determine the affected scope when a fault occurs, provides direction for subsequent operations such as fault location and optical cable life prediction, and improves the comprehensiveness and systematicness of dumb resource management.

Step S4: After locating the fault according to the first optical cable troubleshooting vector identifier of the first risk optical cable, predict the optical cable life according to the fault location result to output a first updated optical cable life of the first risk optical cable, and store the first updated optical cable life in the first optical cable RFID of the first risk optical cable.

Specifically, after identifying risky optical cables, on-site testing equipment (such as an OTDR) conducts testing along the direction and information indicated by the optical cable troubleshooting vector to locate the fault point in the optical cable, thereby obtaining a fault location result. This fault location result includes information such as the specific location of the optical cable fault and the cause of the fault. For example, in an optical cable network, a cable may be damaged at a specific node, resulting in signal interruption. After obtaining the fault location result based on the first optical cable troubleshooting vector, the fault location result is combined with historical optical cable data, such as previous maintenance records, number of faults, and operating environment. A lifespan prediction method similar to that in step S2 (such as an algorithm based on data mining, machine learning, or a physical model) is used to predict the expected remaining lifespan of the optical cable, i.e., the first updated optical cable lifespan. This first updated optical cable lifespan reflects the expected service life of the optical cable in its current state. For example, for an optical cable identified as having minor damage, a physical model-based lifespan prediction method can be used to predict a remaining lifespan of one year based on the damage severity, previous maintenance records, and environmental conditions (such as whether it is frequently affected by external construction). The first updated optical cable life information is stored in the first optical cable RFID through the RFID writer so that subsequent maintenance and management can be planned based on the latest life expectancy.

By accurately predicting the lifespan and updating the data of optical cable resources associated with faulty equipment, the management of the entire life cycle of dumb resources is further improved, which helps to rationally arrange the maintenance and update of resources and improve the reliability and operating efficiency of the entire dumb resource network.

Furthermore, before the first dummy resource fault detection node analyzes and outputs the first dummy resource fault, the method includes:

Step S01: RFID configuration is performed in a dumb resource optical cable topology to obtain K node RFIDs and H optical cable RFIDs, wherein the K node RFIDs are configured on K dumb resource devices in the dumb resource optical cable topology, and the H optical cable RFIDs are configured on H dumb resource optical cables in the dumb resource optical cable topology.

Step S02: performing relay device configuration according to the layout characteristics of the K RFID nodes to obtain K relay identification links.

Step S03: Analyze the relay device coverage of the H optical cable RFIDs according to the K relay identification links, perform relay device compensation according to the analysis results, and output H optical cable identification links.

Step S04: Configure edge fault nodes according to the device types of the K dumb resource devices to obtain M dumb resource fault detection nodes, wherein the K dumb resource devices are communicatively connected with the M dumb resource fault detection nodes based on device consistency, and the M dumb resource fault detection nodes are communicatively connected with the dumb resource fault detection cloud.

Specifically, the dumb resource cable topology refers to the distribution and connection relationships of dumb resources in the optical cable network, including key connection points such as optical cross-connect boxes, fiber splitter boxes, and splice closures, as well as the cable installation paths. When configuring RFID in a dumb resource cable topology, the key connection points in the optical cable network, such as optical cross-connect boxes, fiber splitter boxes, and splice closures, must first be identified. RFID tags are then installed on at least one type of device within these key connection points. Each tag stores information such as the dumb resource device's serial number, model, and installation date, resulting in a node RFID tag. For ease of description and understanding of this solution by those skilled in the art, the number of connection points is represented by K, where K is a positive integer. For example, in a city's optical communication network, there are 100 key connection points, including 50 optical cross-connect boxes, 30 fiber splitter boxes, and 20 splice closures. RFID tags are installed on each of the 50 optical cross-connect boxes, resulting in 50 node RFID tags (K = 50). Simultaneously, RFID tags are installed at appropriate locations on each of the H dumb resource cables in the dumb resource cable topology to store information such as the cable serial number, model, and installation date. Where H is a positive integer representing the number of dumb resource cables. By configuring RFID tags on dumb resource devices and cables, device and cable information can be identified and stored, facilitating information management of the entire dumb resource cable topology.

Analyze the layout characteristics of K node RFIDs, including the geographical location of the node RFIDs, the distance between them, and the connection relationship with other devices. Based on these characteristics, determine the location and number of relay devices that need to be configured, and obtain K relay identification links, each of which connects a different node RFID or connects the node RFID with other related devices. For example, in a certain section of optical cable network, there are 10 node RFIDs distributed on a 10-kilometer-long optical cable, with a node RFID every 1 kilometer. The effective reading range of the RFID reader is 100 meters, so a relay device needs to be installed every 500 meters between every two adjacent node RFIDs, resulting in 10 relay identification links. By rationally configuring relay devices, the coverage range of the RFID reader is expanded, ensuring comprehensive coverage and effective identification of dumb resource devices, and improving the reliability and efficiency of resource identification.

After obtaining K relay identification links, the relay device coverage of H optical cable RFIDs is analyzed to assess the coverage of the K relay identification links for the H optical cable RFIDs, specifically which optical cable RFIDs are effectively covered by the relay devices. Based on the coverage analysis results, relay devices are added to areas with insufficient coverage to ensure that all optical cable RFIDs are effectively identified. For example, by simulating the propagation path and strength of RFID signals, each optical cable RFID is checked to ensure that it is within the effective coverage of the relay device. For example, if the relay device coverage analysis reveals that five optical cable RFIDs are located at the edge of the relay device coverage area, resulting in weak signals, additional relay devices are needed near these five optical cable RFIDs for relay device compensation. After compensation is completed, each dumb resource device is used as the center, and the optical cable connections between the device and other devices are determined. Then, relay identification links for remote RFID automatic identification are analyzed and constructed based on the RFID placement of each optical cable. H optical cable identification links are obtained, each corresponding to an optical cable RFID identification path. Through coverage analysis and compensation of relay equipment, the identification link of optical cable RFID is optimized, ensuring comprehensive coverage and accurate identification of all optical cable resources, and further improving the refinement of dumb resource management.

Based on the device types of K dumb resource devices, such as optical cross-connect boxes, fiber splitter boxes, and splice boxes, edge fault nodes are deployed near the edge of the dumb resource network or at key connection points to monitor the device's operating status and fault conditions. Then, based on the consistency of the K dumb resource devices' device types, these K dumb resource devices are communicatively connected to M dumb resource fault detection nodes. Each edge fault node receives and processes data from devices of the same type to ensure data processing efficiency. Simultaneously, these M dumb resource fault detection nodes establish a communication connection with the dumb resource fault detection cloud to upload fault information to the cloud in real time for processing and analysis. For example, if K = 100, meaning there are 100 dumb resource devices, M = 20 dumb resource fault detection nodes are deployed based on device type and consistency. Each fault detection node is connected to a certain number of devices, such as one node connected to five optical cross-connect boxes, a second node connected to five fiber splitter boxes, and so on. Through the rational configuration of edge fault nodes and communication connections, real-time monitoring and rapid response to dumb resource device faults are achieved, improving the timeliness and accuracy of fault handling and providing strong support for subsequent maintenance and management.

Furthermore, as shown in FIG2 , step S02 includes:

Step S021: interactively obtain the device coverage radius of the relay device.

Step S022: presetting the number of node coverages, and taking the device coverage radius and the number of node coverages as constraints, performing relay device configuration site fitting according to the layout characteristics of the K node RFIDs to obtain a relay device layout array.

Step S023: performing relay identification response analysis on the relay device layout array according to the layout characteristics of the K RFID nodes, and locating the RFID identification center, wherein the fixed RFID reader is deployed at the RFID identification center.

Step S024: constructing the K relay identification links of the K RFID nodes according to the array arrangement of the RFID identification center and the relay device.

Specifically, the relay device's coverage radius is the maximum distance within which the relay device can receive and forward RFID signals within its effective operating range. Within this distance, the relay device ensures that the signal strength and quality meet RFID reading and writing requirements. Obtain the relay device's coverage radius by consulting the relay device manufacturer's technical documentation or conducting field testing.

The preset node coverage number is the maximum number of node RFIDs that a single relay device can effectively cover. Then, based on the layout characteristics of the K node RFIDs, a geometric fitting algorithm or an optimization algorithm is used to determine the layout positions of the relay devices, while satisfying the device coverage radius and node coverage number constraints, to form a relay device layout array. This relay device layout array is a set of relay device layout positions obtained based on the fitting results. For example, a genetic algorithm is used to find relay device configuration sites that meet the conditions. The genetic algorithm simulates the biological evolution process and performs crossover, mutation, and other operations on the initial random layout positions of the relay devices, with the goal of minimizing the number of uncovered nodes. After multiple generations of evolution, a better layout position is found to form a relay device layout array.

Based on the deployment characteristics of K RFID nodes, the relay device array is analyzed for recognition and response. Simulations or actual tests are conducted on the relay device's recognition response to the node RFID at the deployment location to determine the optimal RFID signal recognition location, i.e., the RFID recognition center. In actual implementation, signal propagation models or practical testing tools, such as RFID readers and tag testers, can be used to detect the signal between each relay device in the relay device array and the K RFID nodes. Based on the detected signal strength and recognition success rate from each relay device to each node RFID, a cluster analysis algorithm is used to group relay devices with similar signal strength and recognition success rate into a single cluster. Within each cluster, the RFID recognition center is determined by calculating the cluster center. A fixed RFID reader is then deployed at each RFID recognition center to read and write node RFID information.

Based on the determined RFID identification center and relay device array, with the RFID identification center as the core, the relay devices in the relay device array are connected to the node RFIDs. Based on the principle of optimal signal transmission path (for example, choosing the path with minimal signal attenuation), the link from each node RFID to the identification center is determined. K relay identification links are constructed for K node RFIDs to ensure that each node RFID can be effectively identified and connected through the corresponding relay identification link.

Through the above steps, the reasonable configuration and optimized layout of relay equipment are achieved, and an efficient relay identification link is built, which helps to achieve effective management and data transmission of node RFID, provides an infrastructure for the automatic identification and management of dumb resources, and improves the efficiency and accuracy of dumb resource management.

Furthermore, step S03 includes:

Step S031: constructing a relay device coverage space according to the device coverage radius and the relay device layout array.

Step S032: Align the layout features of the H optical cable RFIDs with the coverage space of the relay device to obtain a plurality of uncovered RFIDs.

Step S033: performing relay device compensation of the relay device layout array according to the multiple uncovered RFIDs to obtain an updated device layout array.

Step S034: constructing the H optical cable identification links of the H optical cable RFIDs according to the array of the RFID identification center and the update device.

Specifically, the relay device coverage space refers to the signal coverage area formed by the device coverage radius of the relay device and the relay device layout array. This space defines the range in which the relay device can effectively receive and forward RFID signals. According to the coverage radius and layout array of the relay device, a spherical space is constructed with each relay device in the relay device layout array as the center of the sphere and the device coverage radius as the radius. These spherical spaces overlap and merge with each other to eventually form an overall relay device coverage space. For example, there are 10 relay devices, each with a coverage radius of 300 meters. By laying out the array, a relay device coverage space is constructed in a certain area. This space is a continuous area composed of multiple circular coverage areas. Clarifying the coverage range of the relay device can provide a basis for subsequent coverage analysis and compensation, ensuring comprehensive coverage of optical cable RFID.

The layout characteristics of optical cable RFIDs refer to the distribution characteristics of H optical cable RFIDs within the optical cable network, including their placement, orientation, density, and connectivity. Comparing the layout characteristics (e.g., coordinates) of the H optical cable RFIDs with the model of the relay device coverage space can identify uncovered optical cable RFIDs (i.e., multiple uncovered RFIDs). This provides clear targets for subsequent relay device compensation and improves coverage integrity. In practical implementation, spatial detection algorithms, such as the ray method or the point-inside-polyhedron detection algorithm (for three-dimensional space), can be used to determine whether each optical cable RFID is within the relay device coverage space. Based on the locations of uncovered RFIDs, optimization algorithms such as simulated annealing and genetic algorithms are used, with the objective function of minimizing the sum of distances from uncovered RFIDs to the nearest relay device. The coordinates of new relay devices are calculated to determine the number and locations of additional relay devices or to adjust the positions of existing relay devices. This ensures that all optical cable RFIDs are effectively identified, improving relay device coverage integrity and reliability. After the relay device compensation is performed, a new relay device arrangement position set is obtained, that is, the device arrangement array is updated.

Based on the RFID identification center and the updated relay device, an array is laid out to construct H optical cable identification links for H optical cable RFIDs, enabling remote reading and transmission of optical cable RFID information. For example, for 50 optical cable RFIDs, 50 optical cable identification links are constructed after compensation, with each link connecting one optical cable RFID to the nearest relay device and passing through the RFID identification center.

Through the above steps, the construction of the relay equipment coverage space, alignment analysis, compensation optimization and the construction of the optical cable identification link were realized, ensuring the comprehensive coverage and effective identification of all optical cable RFIDs, and providing a scientific and reasonable management framework for the refined management of dumb resources.

Furthermore, step S1 includes:

Step S11: locating the device by analyzing the first dumb resource fault to obtain the first dumb resource device.

Step S12: Locate and activate a first relay identification link from the K relay identification links according to the first dumb resource device.

Step S13: Automatically identify the first node RFID corresponding to the first dumb resource device through the first relay identification link to extract the first device history information.

Specifically, a detailed analysis of the first dumb resource fault is performed, and the specific location or identity of the first dumb resource device is determined based on relevant information about the first dumb resource fault (such as the fault location and the device range corresponding to the fault type). If the fault information includes location information (for example, the fault occurred near optical cables or equipment in a specific area), a comparison is performed against a pre-built dumb resource optical cable topology map, and the device connected to that segment is found using the topology map. If the fault information includes information related to the device type or device identifier, a match is directly performed against the list of known dumb resource devices. For example, if the fault information indicates that a specific model of fiber optic splitter box has failed, the device list is searched for that model of fiber optic splitter box as the first dumb resource device.

Based on the location and connection relationship of the first dumb resource device, a search is performed among the K relay identification links to find a link associated with the first dumb resource device and determine it as the first relay identification link. For example, if the first dumb resource device is connected to other devices via a specific optical cable, and this optical cable corresponds to part of a relay identification link, then this relay identification link is determined to be the first relay identification link. After the first relay identification link is determined, an activation signal is sent to activate it.

After the first relay identification link is activated, an RFID identification device (such as an RFID reader) identifies the first node RFID. The RFID reader transmits radio frequency signals to communicate with the first node RFID and receives a return signal. This signal contains the information stored by the first node RFID, from which the first device's historical information is extracted.

Through the above steps, the complete process from fault detection to equipment positioning, to activation of the relay identification link and RFID automatic identification processing is realized, providing the necessary data support for subsequent equipment life prediction and maintenance optimization.

Furthermore, step S2 includes:

Step S21: performing a fault operation and maintenance analysis based on the first dumb resource fault and the first device historical information, and outputting a first operation and maintenance compensation strategy.

Step S22: performing life prediction update according to the first operation and maintenance compensation strategy and the first equipment historical information, and outputting a first updated equipment life.

Step S23: storing the first update device life, the first dumb resource failure, and the first operation and maintenance compensation strategy in the first node RFID.

Specifically, based on the first dumb resource failure and the historical information of the first device, the cause of the failure is analyzed, the impact is assessed, etc., so as to formulate specific measures and plans for the current failure and historical operation and maintenance conditions, and optimize the subsequent operation and maintenance management of the equipment, and store them as the first operation and maintenance compensation strategy. First, an in-depth analysis of the type, severity, frequency of occurrence and other information of the first dumb resource failure is performed. At the same time, the historical information of the first device is retrieved to check whether the device has a similar failure history, as well as the previous handling methods and effects. An operation and maintenance compensation strategy is formulated based on the analysis results. In the actual implementation process, the operation and maintenance compensation strategy can be formulated by referring to resources such as the technical manual of the device and the operation and maintenance experience knowledge base. For example, the operation and maintenance experience knowledge base records common solutions for different types of failures of the device, and the appropriate operation and maintenance strategy is determined by querying the knowledge base.

Based on the first O&M compensation strategy (such as repairs and component replacements) and the first device's historical information (existing operating hours, previous maintenance records, etc.), the remaining useful life of the first dummy resource device is re-evaluated to obtain an updated device life, namely the first updated device life. First, the existing device life prediction model is adjusted based on the first O&M compensation strategy. For example, if the first O&M compensation strategy involves replacing a key component of the device, the corresponding life parameters in the life prediction model need to be updated. Assume the original device life prediction model is L = L ₀ - kT - mF (where L is the remaining life, L ₀ is the initial life, T is the operating time, F is the number of failures, and k and m are coefficients). If a key component is replaced with an initial life of L _new , the new life prediction model becomes L = L _new + (L ₀ - kT - mF). After obtaining the new life prediction model, the data in the first device's historical information (such as operating time and number of failures) is substituted into the adjusted life prediction model for calculation to obtain the first updated device life. For example, it is known that the equipment has been running for T = 1000 hours and has experienced F = 5 failures. The value of L calculated according to the new life prediction model is the first updated equipment life.

Information such as the first updated device lifespan, the first dumb resource failure, and the first operation and maintenance compensation strategy is written to the first node RFID using an RFID writer. This facilitates subsequent automatic identification and management, enabling real-time updating and sharing of device information. During the writing process, the accuracy and completeness of the write operation must be ensured. The correctness of the written information can be ensured through mechanisms such as checksum verification. For example, after writing the information, the information in the first node RFID is read again and compared with the original written information. If any discrepancies are found, the information is rewritten.

Through the above steps, accurate operation and maintenance analysis of faulty equipment, life prediction updates and efficient storage of information are achieved, which helps to improve the reliability and operation efficiency of dumb resource equipment, provides a scientific basis and real-time data support for subsequent equipment management and maintenance, and further improves the level of refinement of dumb resource management.

Furthermore, step S3 includes:

Step S31: Fault information is filtered according to the first upload timestamp of the first dumb resource fault and the dumb resource optical cable topology, and a second dumb resource fault is output.

Step S32: The second dumb resource device and the second upload timestamp corresponding to the second dumb resource failure are indexed and called in the dumb resource identification cloud.

Step S33: extracting the first risk optical cable from the dumb resource optical cable topology according to the second dumb resource device and the first dumb resource device.

Step S34: Calculate and output the first optical cable troubleshooting vector based on the first upload timestamp and the second upload timestamp.

Specifically, based on the first upload timestamp of the first dumb resource fault, as well as the fiber optic cable connections and node information related to the fault in the dumb resource fiber optic cable topology, other fault information related to the current fault is filtered out from the numerous fault information within a certain time range (e.g., within an hour before and after), and output as the second dumb resource fault. Database query tools, such as SQL, can be used to filter by combining timestamps and topological relationships. For example, in an SQL query, using the timestamp field and device location field as filtering criteria, if the upload timestamp of the first dumb resource fault is 2023-10-12 10:00:00, other faults occurring between 2023-10-12 09:00:00 and 2023-10-12 11:00:00 in the dumb resource fiber optic cable topology are filtered out as the second dumb resource fault. By filtering by timestamp and topology, other faults that may be related to the current fault can be discovered, providing more comprehensive information for subsequent risk fiber optic cable extraction and improving the accuracy of fault analysis.

The second dumb resource device refers to the device associated with the second dumb resource failure. The second upload timestamp is the time stamp when the second dumb resource failure information is uploaded to the cloud. In the dumb resource identification cloud database, an index is retrieved based on the second dumb resource failure information (such as failure location and time) to obtain the corresponding second dumb resource device and second upload timestamp.

In the dumb resource optical cable topology, the connection relationship between the first dumb resource device and the second dumb resource device is searched, including both directly connected and indirectly connected optical cables. The optical cable that connects the two devices is identified as the first risk optical cable. For example, if the first dumb resource device and the second dumb resource device are directly connected via an optical cable, or if both devices are connected to the same intermediate node and share an optical cable, this optical cable can be identified as the first risk optical cable.

Calculate the difference between the first upload timestamp and the second upload timestamp. For example, if the first upload timestamp is _t1 and the second upload timestamp is _t2 , calculate Δt = _t1 - _t2 . Construct a cable troubleshooting vector based on the timestamp difference. If Δt > 0, indicating that the first dumb resource fault occurred before the second dumb resource fault, the direction of the cable troubleshooting vector is from the cable area where the first dumb resource device is located to the cable area where the second dumb resource device is located. If Δt < 0, the direction is the opposite. The specific value and meaning of the vector can be determined based on the actual cable topology and fault distribution. For example, on a two-dimensional cable topology plane, the direction and magnitude of the cable troubleshooting vector can be represented by (x, y) coordinates, where the x and y values are determined based on the timestamp difference and the geometric relationship of the cable topology.

Through the above steps, the complete process from fault information screening to risky optical cable extraction and optical cable troubleshooting vector construction is realized. It can not only discover other faults related to the current fault, but also accurately identify risky optical cables and construct troubleshooting vectors, providing specific direction guidance for subsequent fault handling and optical cable maintenance, and further improving the accuracy of dumb resource maintenance management.

Furthermore, step S4 includes:

Step S41: using the first optical cable troubleshooting vector as a constraint, using an optical time domain reflectometer to troubleshoot and locate the first risk optical cable, and outputting first optical cable fault information.

Step S42: using the first risk optical cable to traverse the H optical cable identification links, and locating the first optical cable identification link.

Step S43: automatically identifying the first optical cable RFID corresponding to the first risky optical cable by activating the first optical cable identification link to extract first optical cable history information.

Step S44: performing life attenuation prediction based on the first optical cable history information and the first optical cable fault information, and outputting the first updated optical cable life.

Step S45: storing the first updated optical cable life in the first optical cable RFID.

Specifically, an optical time-domain reflectometer (OTDR) is an instrument used to measure the location and characteristics of optical cable faults. It transmits light pulses into the cable and receives the reflected light to determine the location of faults, such as breaks and losses, within the cable. The first optical cable fault information refers to detailed information about the fault location and type, obtained through OTDR testing, regarding the first-risk optical cable. OTDR test parameters, such as test wavelength, pulse width, and measurement range, are set based on the cable type and test requirements. The OTDR test start point and direction are determined based on the first optical cable troubleshooting vector. For example, if the first optical cable troubleshooting vector indicates troubleshooting from one end of the cable to the other, connect the OTDR to the corresponding ends of the cable and start the measurement. During the test, the OTDR displays a curve of the reflected signal. By analyzing the abnormal points in the curve, the fault location and type of the first-risk optical cable are determined, and the first optical cable fault information is output. The OTDR's precise measurement can quickly and accurately locate the fault location and type within the optical cable, providing clear guidance for subsequent repair work and reducing troubleshooting time and costs.

Using the information of the first risk optical cable, a traversal search is performed in H optical cable identification links, each element in the optical cable identification link is accessed one by one, and an identification link associated with the first risk optical cable is found and determined to be the first optical cable identification link.

By activating the first optical cable identification link, the RFID reader automatically identifies the first optical cable's RFID tag. The RFID reader sends a radio frequency signal through the first optical cable identification link, activating the first optical cable's RFID tag. The tag returns stored information, which the reader receives and reads, extracting historical information about the first optical cable, including the cable's installation date and maintenance records.

Based on the first optical cable's historical information and the first optical cable's fault information, the optical cable life prediction model is adjusted. The first optical cable's historical information is substituted into the adjusted life prediction model for calculation to obtain a first updated optical cable life. An RFID reader/writer is used to write the first updated optical cable life information to the first optical cable's RFID tag, facilitating centralized management of optical cable information and subsequent querying. The specific implementation process is similar to obtaining the first updated device life, and can be referenced in the aforementioned related description.

Through the above steps, the first-risk optical cable is troubleshooting, link location identification, automatic identification processing, life prediction and information update are realized. This not only improves the efficiency and accuracy of optical cable fault handling, but also provides a scientific basis and real-time data support for the maintenance and update of optical cables, further improving the level of dumb resource management.

Furthermore, the method described in the embodiment of the present application also includes:

Step S51: the dumb resource identification cloud locates the second node RFID according to the second dumb resource device.

Step S52: extracting a second updated device lifetime from the second node RFID.

Step S53: performing deviation calculation on the life of the first update device, the life of the second update device, and the life of the first update optical cable, and outputting a life deviation coefficient.

Step S54: If the lifetime deviation coefficient meets the preset deviation threshold, the first update device lifetime, the second update device lifetime and the first update optical cable lifetime are sequenced, and the shortest lifetime parameter is extracted according to the sequence result.

Step S55: The dummy resource identification cloud sends the shortest lifespan parameter to the first node RFID, the second node RFID and the first optical cable RFID via the M dummy resource fault detection nodes to update the dummy resource lifecycle.

Specifically, in the dumb resource identification cloud, the location or identity of the corresponding second node RFID is determined based on relevant information about the second dumb resource device (e.g., device identification, device location, etc.). For example, a search can be performed by querying a cloud database, using the identification information of the second dumb resource device (e.g., device number) as a keyword.

An RFID reader communicates with the second node RFID and reads the second update device lifetime information stored therein from the second node RFID. The differences between the first update device lifetime, the second update device lifetime, and the first update optical cable lifetime are calculated to obtain a lifetime deviation coefficient. The lifetime deviation coefficient reflects the degree of deviation between the first update device lifetime, the second update device lifetime, and the first update optical cable lifetime; a larger value indicates a greater degree of deviation. First, the difference between the first update device lifetime _L1 and the second update device lifetime _L2 is calculated as _ΔL12 = _L1 - _L2 ; the difference between the first update device lifetime _L1 and the first update optical cable lifetime _L3 is calculated as _ΔL13 = _L1 - _L3 ; and the difference between the second update device lifetime _L2 and the first update optical cable lifetime _L3 is calculated as _ΔL23 = _L2 - _L3 . Based on these differences, the lifetime deviation coefficient C is calculated, for example, C = (|ΔL12| + |ΔL13| + |ΔL23|) / (L1 + L2 + L3).

The preset deviation threshold is a pre-set value used to measure whether the lifetime deviation coefficient is within an acceptable range. The calculated lifetime deviation coefficient C is compared with the preset deviation threshold T. If C ≤ T, the lifetime deviation between the three is within an acceptable range. The first update device lifetime _L1 , the second update device lifetime _L2 , and the first update optical cable lifetime _L3 are combined into an array ( _L1 , _L2 , _L3 ). Then, a sorting algorithm (such as a bubble sort algorithm) is used to sort the elements in the array in ascending order. Based on the sorted result, the first element in the array is extracted as the shortest lifetime parameter.

The dumb resource identification cloud updates the lifecycle information of the dumb resources (devices or optical cables) corresponding to the first node RFID, the second node RFID, and the first optical cable RFID using the minimum lifetime parameter to reflect the latest lifecycle status. The dumb resource identification cloud first formats and encapsulates the minimum lifetime parameter for network transmission. For example, it converts the minimum lifetime parameter into a specific data packet format and adds the target RFID's identification information. M dumb resource fault detection nodes receive the data packet from the cloud. Each node forwards the data packet to the next node based on its routing strategy and network connectivity, or directly sends it to the device or optical cable area where the target RFID is located. These nodes can utilize network communication protocols (such as TCP/IP) to ensure reliable data transmission. After receiving the data packet containing the minimum lifetime parameter, the first node RFID, the second node RFID, and the first optical cable RFID update their stored lifecycle information. For example, if the minimum lifetime parameter is a value in hours, this value is updated in the corresponding field storing the remaining life of the device or optical cable. This update can be accomplished using the RFID's write function.

The above steps evaluate the health of devices and cables by calculating the lifespan deviation coefficient and intelligently sorting lifespan data. This prioritizes maintenance of the most vulnerable devices, thereby reducing the overall risk of failure in the dumb resource network. Simultaneously, lifecycle updates are automatically synchronized, improving the intelligence of dumb resource management and maintenance decisions and ensuring the long-term stable operation of the entire dumb resource network.

In summary, the method for managing the lifecycle of dumb resources supporting RFID automatic identification provided by the embodiments of the present application has the following beneficial effects:

The embodiment of the present application constructs a digital identification foundation for dumb resources by performing RFID configuration in the dumb resource optical cable topology, including installing RFID tags on K dumb resource devices and H dumb resource optical cables. On this basis, the coverage of the RFID reader is expanded through relay device configuration and link analysis compensation, ensuring comprehensive coverage and effective identification of all dumb resource devices and optical cables. At the same time, through reasonable edge fault node configuration and communication connection, real-time monitoring and rapid response to dumb resource device failures are achieved. Furthermore, through fault operation and maintenance analysis and life prediction updates, the scientific nature of equipment maintenance and the refinement of resource management are improved. Through optical cable fault detection and information updates, efficient maintenance and management of optical cable resources are ensured. Subsequently, the cloud further uses the data of the second dumb resource device, comprehensively calculates the life deviation coefficient of the first and second devices and optical cables, determines whether there is abnormal aging, and extracts the shortest life parameter when the deviation exceeds the threshold, and sends it to the dumb resource fault detection node to complete the dumb resource life cycle update.

Overall, the embodiments of this application, through the introduction of RFID automatic identification technology, achieve rapid detection and location of dumb resource faults. This technology combines the dumb resource's historical operation and maintenance data with its current fault conditions to predict its lifespan, improving the accuracy of lifespan predictions. Secondly, by correlating dumb resource faults with associated risky optical cables, comprehensive management from dumb resources to optical cables is achieved, improving the efficiency and accuracy of dumb resource fault handling, thereby significantly improving dumb resource management efficiency and resource utilization, and enabling refined management of dumb resources.

In the second embodiment, as shown in FIG3 , based on the same inventive concept as in the first embodiment, the present embodiment provides a dumb resource lifecycle management system supporting RFID automatic identification, the system comprising:

The relay identification link activation module 10 is used to activate the relay identification link according to the first dumb resource fault after the first dumb resource fault detection node analyzes and outputs the first dumb resource fault, so as to automatically identify the first node RFID corresponding to the first dumb resource fault and extract the first device history information, wherein the RFID automatic identification is achieved through the collaborative work of a fixed RFID reader and a relay device.

The life decay prediction module is used to perform life decay prediction based on the first dummy resource failure and the first device history information, output a first updated device life, and store the first updated device life to the first node RFID.

The associated risk optical cable screening module 30 is used for dumb resource identification. After receiving the first dumb resource fault, the cloud performs associated risk optical cable screening according to the first upload timestamp of the first dumb resource fault to locate the first risk optical cable.

The optical cable life prediction module 40 is used to locate the fault according to the first optical cable troubleshooting vector identifier of the first risk optical cable, predict the optical cable life according to the fault location result, output the first updated optical cable life of the first risk optical cable, and store the first updated optical cable life in the first optical cable RFID of the first risk optical cable.

Furthermore, the system described in the embodiment of the present application further includes a relay link construction module, and the relay link construction module is configured to perform the following steps:

RFID is configured in the dumb resource optical cable topology to obtain K node RFIDs and H optical cable RFIDs, wherein the K node RFIDs are configured in K dumb resource devices in the dumb resource optical cable topology, and the H optical cable RFIDs are configured in H dumb resource optical cables in the dumb resource optical cable topology; relay device configuration is performed according to the layout characteristics of the K node RFIDs to obtain K relay identification links; relay device coverage of the H optical cable RFIDs is analyzed according to the K relay identification links, and relay device compensation is performed according to the analysis results to output H optical cable identification links; edge fault node configuration is performed according to the device type of the K dumb resource devices to obtain M dumb resource fault detection nodes, wherein the K dumb resource devices are communicatively connected to the M dumb resource fault detection nodes based on device consistency, and the M dumb resource fault detection nodes are communicatively connected to the dumb resource fault detection cloud.

Furthermore, the relay link construction module is further configured to perform the following steps:

Interactively obtain the device coverage radius of the relay device; preset the number of node coverage, and with the device coverage radius and the number of node coverage as constraints, perform relay device configuration site fitting according to the layout characteristics of the K node RFIDs to obtain a relay device layout array; perform relay identification response analysis on the relay device layout array according to the layout characteristics of the K node RFIDs, and locate the RFID identification center, wherein the fixed RFID reader is deployed in the RFID identification center; based on the RFID identification center and the relay device layout array, construct the K relay identification links of the K node RFIDs.

Furthermore, the relay link construction module is further configured to perform the following steps:

A relay device coverage space is constructed based on the device coverage radius and the relay device layout array; the layout characteristics of the H optical cable RFIDs are aligned with the relay device coverage space to obtain multiple uncovered RFIDs; relay device compensation of the relay device layout array is performed based on the multiple uncovered RFIDs to obtain an updated device layout array; and the H optical cable identification links of the H optical cable RFIDs are constructed based on the RFID identification center and the updated device layout array.

Furthermore, in the embodiment of the present application, the relay identification link activation module 10 is further configured to perform the following steps:

The device is located by analyzing the first dumb resource fault to obtain the first dumb resource device; the first relay identification link is located and activated from the K relay identification links according to the first dumb resource device; the first node RFID corresponding to the first dumb resource device is automatically identified and processed through the first relay identification link to extract the first device historical information.

Furthermore, the equipment life prediction module 20 of the embodiment of the present application is further configured to perform the following steps:

Perform a fault operation and maintenance analysis based on the first dumb resource failure and the first device historical information, and output a first operation and maintenance compensation strategy; perform a life prediction update based on the first operation and maintenance compensation strategy and the first device historical information, and output a first updated device life; store the first updated device life, the first dumb resource failure, and the first operation and maintenance compensation strategy to the first node RFID.

Furthermore, the risk-associated optical cable screening module 30 in the embodiment of the present application is further configured to perform the following steps:

Fault information is screened based on the first upload timestamp of the first dumb resource fault and the dumb resource optical cable topology, and a second dumb resource fault is output; the second dumb resource device and the second upload timestamp corresponding to the second dumb resource fault are called in the dumb resource identification cloud index; the first risk optical cable is extracted in the dumb resource optical cable topology based on the second dumb resource device and the first dumb resource device; the first optical cable troubleshooting vector is calculated and output based on the first upload timestamp and the second upload timestamp.

Furthermore, the optical cable life prediction module 40 of the embodiment of the present application is further configured to perform the following steps:

Taking the first optical cable troubleshooting vector as a constraint, use an optical time domain reflectometer to troubleshoot and locate the first risk optical cable, and output first optical cable fault information; use the first risk optical cable to traverse the H optical cable identification links to locate the first optical cable identification link; automatically identify and process the first optical cable RFID corresponding to the first risk optical cable by activating the first optical cable identification link to extract the first optical cable history information; perform life attenuation prediction based on the first optical cable history information and the first optical cable fault information, and output the first updated optical cable life; store the first updated optical cable life in the first optical cable RFID.

Furthermore, the system of the embodiment of the present application further includes a lifecycle update module, which is configured to perform the following steps:

The dumb resource identification cloud locates the second node RFID according to the second dumb resource device; extracts the second update device life from the second node RFID; calculates the deviation of the first update device life, the second update device life and the first update optical cable life, and outputs the life deviation coefficient; if the life deviation coefficient meets the preset deviation threshold, the first update device life, the second update device life and the first update optical cable life are serialized, and the shortest life parameter is extracted according to the sorting result; the dumb resource identification cloud sends the shortest life parameter to the first node RFID, the second node RFID and the first optical cable RFID via the M dumb resource fault detection nodes to update the dumb resource life cycle.

Through the above detailed description of the dumb resource lifecycle management method that supports RFID automatic identification in this specification, those skilled in the art can clearly understand the dumb resource lifecycle management system that supports RFID automatic identification in this embodiment. For the system disclosed in Example 2, since it corresponds to the method disclosed in Example 1 and has corresponding functional modules and beneficial effects, the relevant details can be referred to the method section.

The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present application. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application is not limited to the embodiments shown herein, but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims (10)

1. The dummy resource life cycle management method supporting RFID automatic identification is characterized by comprising the following steps:

After a first dummy resource fault detection node analyzes and outputs a first dummy resource fault, activating a relay identification link according to the first dummy resource fault so as to automatically identify a first node RFID corresponding to the first dummy resource fault and extract first equipment history information, wherein the RFID automatic identification is realized through the cooperative work of a fixed RFID reader-writer and relay equipment;

Performing life attenuation prediction according to the first dummy resource fault and the first equipment history information, outputting first updated equipment life, and storing the first updated equipment life to the first node RFID;

After receiving the first dummy resource fault, the dummy resource identification cloud performs associated risk optical cable screening according to a first uploading time stamp of the first dummy resource fault, and positions a first risk optical cable;

After fault location is performed according to the first cable troubleshooting vector identification of the first risk cable, the first updated cable life of the first risk cable is output in a predicted mode according to the fault location result, and the first updated cable life is stored in the first cable RFID of the first risk cable.

2. The method for managing a life cycle of a dummy resource supporting RFID automatic identification according to claim 1, wherein before the first dummy resource failure detection node analyzes and outputs the first dummy resource failure, the method comprises:

performing RFID configuration on a dummy resource optical cable topology to obtain K node RFID and H optical cable RFID, wherein the K node RFID is configured on K dummy resource devices in the dummy resource optical cable topology, and the H optical cable RFID is configured on H dummy resource optical cables in the dummy resource optical cable topology;

performing relay equipment configuration according to the layout characteristics of the K node RFID to obtain K relay identification links;

performing coverage analysis on the relay equipment of the H optical cable RFID according to the K relay identification links, performing relay equipment compensation according to an analysis result, and outputting H optical cable identification links;

And configuring edge fault nodes according to the equipment types of the K pieces of dummy resource equipment to obtain M pieces of dummy resource fault detection nodes, wherein the K pieces of dummy resource equipment are in communication connection with the M pieces of dummy resource fault detection nodes based on equipment consistency, and the M pieces of dummy resource fault detection nodes are in communication connection with a dummy resource fault detection cloud.

3. The method for managing the life cycle of the dummy resource supporting the automatic identification of the RFID according to claim 2, wherein the relay device is configured according to the layout characteristics of the RFIDs of the K nodes to obtain K relay identification links, the method comprising:

Interactively obtaining the equipment coverage radius of the relay equipment;

presetting node coverage quantity, taking the equipment coverage radius and the node coverage quantity as constraints, and fitting relay equipment configuration sites according to the layout characteristics of the K node RFID to obtain a relay equipment layout array;

According to the layout characteristics of the K node RFID, carrying out relay identification response analysis on the relay equipment layout array, and positioning an RFID identification center, wherein the fixed RFID reader-writer is arranged in the RFID identification center;

and constructing the K relay identification links of the K node RFID according to the RFID identification center and the relay equipment layout array.

4. The method for managing a dummy resource life cycle supporting RFID automatic identification according to claim 3, wherein the relay device coverage analysis of the H optical cable RFIDs is performed according to the K relay identification links, and the relay device compensation is performed according to the analysis result, and the H optical cable identification links are output, the method comprising:

constructing a relay equipment coverage space according to the equipment coverage radius and the relay equipment layout array;

aligning the layout characteristics of the H optical cable RFID with the coverage space of the relay equipment to obtain a plurality of uncovered RFID;

Performing relay equipment compensation of the relay equipment layout array according to the plurality of uncovered RFID to obtain an updated equipment layout array;

and constructing the H optical cable identification links of the H optical cable RFID according to the RFID identification center and the updating equipment layout array.

5. The method for managing the life cycle of a dummy resource supporting RFID automatic identification according to claim 2, after the first dummy resource failure detection node analyzes and outputs the first dummy resource failure, performing relay identification link activation according to the first dummy resource failure to automatically identify the first node RFID corresponding to the first dummy resource failure, and extracting the first device history information, the method comprising:

performing equipment positioning by analyzing the first dummy resource fault to obtain first dummy resource equipment;

positioning and activating a first relay identification link from the K relay identification links according to the first dummy resource equipment;

and automatically identifying the first node RFID corresponding to the first dummy resource equipment through the first relay identification link so as to extract the first equipment history information.

6. The method for managing a life cycle of a dummy resource supporting RFID automatic identification according to claim 5, wherein life-cycle decay prediction is performed based on the first dummy resource failure and first device history information, a first updated device life is output, and the first updated device life is stored to the first node RFID, the method comprising:

performing fault operation and maintenance analysis according to the first dummy resource fault and the first equipment history information, and outputting a first operation and maintenance compensation strategy;

Performing life prediction updating according to the first operation and maintenance compensation strategy and the first equipment history information, and outputting a first updated equipment life;

and storing the service life of the first updating equipment, the failure of the first dummy resource and the first operation and maintenance compensation strategy to the first node RFID.

7. The method for managing a life cycle of a dummy resource supporting automatic RFID identification according to claim 2, wherein the dummy resource identification cloud performs associated risk optical cable screening according to a first uploading timestamp of the first dummy resource failure after receiving the first dummy resource failure, and locates a first risk optical cable, the method comprising:

performing fault information screening according to the first uploading time stamp of the first dummy resource fault and the dummy resource optical cable topology, and outputting a second dummy resource fault;

Invoking a second dummy resource device and a second uploading time stamp corresponding to the second dummy resource fault in the dummy resource identification cloud index;

extracting the first risk optical cable in the dummy resource optical cable topology according to the second dummy resource equipment and the first dummy resource equipment;

and calculating and outputting the first optical cable checking vector according to the first uploading time stamp and the second uploading time stamp.

8. The method for managing a dummy resource life cycle supporting RFID automatic identification according to claim 2, wherein after performing fault location according to a first cable troubleshooting vector identification of the first risk cable, performing cable life prediction according to a fault location result to output a first updated cable life of the first risk cable, and storing the first updated cable life in a first cable RFID of the first risk cable, the method comprising:

Taking the first optical cable troubleshooting vector as constraint, performing troubleshooting positioning on the first risk optical cable by using an optical time domain reflectometer, and outputting first optical cable fault information;

Traversing the H optical cable identification links by adopting the first risk optical cable, and positioning the first optical cable identification links;

the first cable RFID corresponding to the first risk cable is automatically identified by activating the first cable identification link so as to extract first cable history information;

Performing life attenuation prediction according to the first optical cable history information and the first optical cable fault information, and outputting the first updated optical cable life;

storing the first updated cable life to the first cable RFID.

9. The method for managing a dummy resource lifecycle supporting RFID automatic identification of claim 7, further comprising:

The dummy resource identification cloud end locates a second node RFID according to the second dummy resource equipment;

extracting a second updated device lifetime from the second node RFID;

performing deviation calculation on the service life of the first updating equipment, the service life of the second updating equipment and the service life of the first updating optical cable, and outputting a service life deviation coefficient;

If the life deviation coefficient meets a preset deviation threshold, serializing the life of the first updating equipment, the life of the second updating equipment and the life of the first updating optical cable, and extracting the shortest life parameter according to the sorting result;

and the dummy resource identification cloud transmits the shortest service life parameter to the first node RFID, the second node RFID and the first optical cable RFID through the M dummy resource fault detection nodes to update the dummy resource life cycle.

10. A dummy resource lifecycle management system supporting RFID automatic identification, the system being configured to perform the dummy resource lifecycle management method supporting RFID automatic identification of any one of claims 1-9, comprising:

The relay identification link activation module is used for activating a relay identification link according to the first dummy resource fault after the first dummy resource fault detection node analyzes and outputs the first dummy resource fault so as to automatically identify the first node RFID corresponding to the first dummy resource fault and extract the first equipment history information, wherein the RFID automatic identification is realized through the cooperative work of a fixed RFID reader-writer and relay equipment;

The equipment life prediction module is used for carrying out life attenuation prediction according to the first dummy resource fault and the first equipment history information, outputting a first updated equipment life and storing the first updated equipment life to the first node RFID;

the associated risk optical cable screening module is used for carrying out associated risk optical cable screening according to a first uploading time stamp of the first dummy resource fault after the dummy resource identification cloud receives the first dummy resource fault, and positioning a first risk optical cable;

And the optical cable life prediction module is used for predicting the life of the optical cable according to the fault positioning result to output the life of the first updated optical cable of the first risk optical cable after the fault positioning is carried out according to the first optical cable troubleshooting vector identification of the first risk optical cable, and storing the life of the first updated optical cable in the first optical cable RFID of the first risk optical cable.