SDH communication equipment fault maintenance simulation teaching method and system based on digital twinning

Abstract

The invention discloses an SDH communication equipment fault maintenance simulation teaching method based on digital twinning. The method comprises the following steps of S1, equipment simulation, S2, fault scene definition, S3, fault injection, S4, fault simulation, S5, fault diagnosis, S6, fault repair and S7, evaluation and feedback. The system has the advantages that a real SDH equipment fault scene can be simulated, fault checking and repairing training close to actual combat can be provided for students, excessive consumption and high purchase cost of entity equipment are avoided, virtual simulation of an SDH communication equipment fault mode is realized by constructing a high-precision SDH communication equipment digital twinborn body, and the simulation efficiency of the SDH communication equipment fault mode is improved. And fault processing training close to a real environment is provided for students. The invention provides an efficient, economic and safe SDH communication equipment fault maintenance skill training method so as to improve the practical ability and the troubleshooting efficiency of trainees.

Description

Technical field:

[0001] The present invention relates to the field of equipment fault maintenance simulation teaching, and in particular to a SDH communication equipment fault maintenance simulation method based on digital twin. Background technology:

[0002] With the rapid development of communication technology, optical fiber communication transmission equipment is the key infrastructure of optical fiber communication network, and plays the role of the thrust pump of communication traffic transmission in optical fiber communication network. The rapid development of optical communication transmission equipment technology has become the engine to promote the rapid development of ICT era. Among them, SDH equipment, as the core equipment of transmission network, has been widely used in power, finance, telecommunications and other industries, and its technology has also developed rapidly. At the same time, timely troubleshooting and repair of SDH equipment failures has become particularly important. In order to improve the troubleshooting and repair skills of SDH equipment failures, students are usually organized to conduct relevant teaching and training.

[0003] At present, the teaching of SDH communication equipment fault maintenance mainly relies on physical entity equipment. This method has the following significant disadvantages:

[0004] 1. Limited resources: One physical device can only simulate one fault mode at a time, which limits the number of trainees and reduces teaching efficiency. 2. High equipment wear and tear: Repeated simulation of fault modes causes excessive consumption of physical equipment, shortens the service life of the equipment, and increases maintenance costs. 3. High purchase cost: High-quality SDH communication equipment is expensive, and large-scale purchases will significantly increase the operating costs of teaching institutions. 4. Single fault mode: It is difficult for physical equipment to fully cover all possible fault modes, which limits trainees' training in complex fault handling. Summary of the invention:

[0005] In order to solve the above problems, the first purpose of the present invention is to provide an SDH communication equipment fault maintenance simulation teaching method based on digital twin. The second purpose of the present invention is to provide an SDH communication equipment fault maintenance simulation teaching system based on digital twin. By constructing a high-precision digital twin of SDH communication equipment, virtual simulation of the failure mode of SDH communication equipment is realized, providing trainees with fault handling training close to the real environment.

[0006] The first object of the present invention is implemented by the following technical solutions:

[0007] The SDH communication equipment fault maintenance simulation teaching method based on digital twin includes the following steps:

[0008] S1. Equipment simulation: Based on the basic parameters of the real equipment (physical characteristics, working principles, parameter settings, etc.), a high-precision virtual SDH communication equipment model is constructed to simulate the normal operation of the SDH communication equipment;

[0009] S2, fault scenario definition: setting different characteristic parameters (fault parameters, fault types, fault occurrence time and duration, etc.) on the virtual SDH communication equipment model to define various possible fault scenarios and obtain a fault test model;

[0010] S3, fault injection: introduce preset fault conditions (which can be software-level (such as memory leaks, dead loops, etc.) or hardware-level (such as power fluctuations, signal interference, etc.)) into the fault test model to simulate various abnormal conditions that the system may encounter in actual operation;

[0011] S4, Fault simulation: Based on the injected fault conditions, simulate the operating state and response of the fault test model under these fault conditions;

[0012] S5, Fault diagnosis: According to the fault location algorithm, comprehensive fault detection and diagnosis are carried out to determine the type, location and possible cause of the fault, and output the diagnosis results;

[0013] S6, Fault repair: Based on the diagnosis results, the trainees formulate corresponding repair plans and perform repair operations;

[0014] S7. Evaluation and feedback: Use the teaching evaluation feedback algorithm to evaluate the students' fault repair solutions and repair operations, and provide feedback.

[0015] Furthermore, the S1, device simulation comprises the following steps:

[0016] S11. Data collection and integration: Collect fault status data of physical equipment, integrate performance parameters of physical equipment, and achieve a high degree of simulation of fault status response of physical equipment;

[0017] S12. Simulation model construction: Use three-dimensional modeling technology to construct a virtual SDH communication equipment model including the equipment appearance, internal structure, and connection relationship.

[0018] Furthermore, the characteristic parameters in the S2, fault scenario definition, include fault parameters, fault type, fault occurrence time and duration.

[0019] Furthermore, the fault location algorithm in the fault diagnosis in S5 adopts the path tracing Dijkstra algorithm.

[0020] Furthermore, the teaching evaluation feedback algorithm in the evaluation feedback in S7 adopts a fuzzy comprehensive evaluation method.

[0021] The second object of the present invention is implemented by the following technical solutions:

[0022] The SDH communication equipment fault maintenance simulation teaching system based on digital twin includes:

[0023] S1, Equipment simulation module: Based on the basic parameters of the real equipment, a high-precision virtual SDH communication equipment model is constructed to simulate the normal operation of the SDH communication equipment;

[0024] S2, fault scenario definition module: setting different characteristic parameters on the virtual SDH communication device model to define various possible fault scenarios and obtain a fault test model;

[0025] S3, fault injection module: introduces preset fault conditions into the fault test model to simulate various abnormal conditions that the system may encounter in actual operation;

[0026] S4, fault simulation module: based on the injected fault conditions, simulate the operating state and response of the fault test model under these fault conditions;

[0027] S5, fault diagnosis module: according to the fault location algorithm, conduct comprehensive fault detection and diagnosis, determine the type, location and possible cause of the fault, and output the diagnosis result;

[0028] S6, Fault repair module: Based on the diagnosis results, students formulate corresponding repair plans and perform repair operations;

[0029] S7, Evaluation and feedback module: Use the teaching evaluation and feedback algorithm to evaluate the students' fault repair solutions and repair operations, and provide feedback.

[0030] Advantages of the present invention:

[0031] The present invention proposes a technical method for a virtual simulation system for teaching fault maintenance of SDH communication equipment based on a digital twin model, aiming to solve the problems of limited resources, large equipment loss, and high purchase cost in existing physical equipment teaching methods, and to provide a new, efficient, and low-cost solution for teaching fault maintenance of SDH communication equipment.

[0032] The present invention aims to build a highly simulated SDH (Synchronous Digital Hierarchy) communication equipment fault maintenance simulation teaching system through digital twin technology. The system can simulate real SDH equipment fault scenarios, provide students with close-to-actual combat fault troubleshooting and repair training, while avoiding excessive consumption of physical equipment and high purchase costs. By building a high-precision SDH communication equipment digital twin, the virtual simulation of SDH communication equipment failure mode is realized, providing students with fault handling training close to the real environment. Provide an efficient, economical and safe SDH communication equipment fault maintenance skills training method to improve students' practical ability and troubleshooting efficiency. Description of the drawings:

[0033] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0034] Figure 1 This is a schematic diagram of the Dijkstra algorithm principle in Example 2;

[0035] Figure 2 It is a flowchart of the Dijkstra algorithm in Example 2;

[0036] Figure 3 This is a basic flow chart of the "fuzzy comprehensive evaluation" algorithm in the embodiment. Specific implementation method:

[0037] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] Embodiment 1:

[0039] The SDH communication equipment fault maintenance simulation teaching system based on digital twin includes the following modules:

[0040] 1. "Device simulation module" and "fault scenario definition module"

[0041] In equipment fault maintenance teaching or actual equipment fault simulation system based on virtual simulation technology, there is a close logical relationship between "equipment simulation module" and "fault scenario definition module". This relationship is mainly reflected in the following aspects:

[0042] 1) Interdependence

[0043] ●Device simulation module is the basis:

[0044] The device simulation module is the core foundation of the entire simulation system. It uses computer technology to build a high-precision virtual device model based on the physical characteristics, working principles, parameter settings, etc. of the real device. It can accurately simulate the appearance, interface, configuration and operating status of SDH communication equipment (such as terminal multiplexer TM, add-drop multiplexer ADM, regeneration repeater REG, synchronous digital cross-connection equipment SDXC, etc.); it can accurately simulate the behavioral characteristics of the device in various operating states, including normal operating state, abnormal state and fault state.

[0045] ●The fault scenario definition module depends on the device simulation module:

[0046] The fault scenario definition module works after the device simulation module successfully builds the virtual device model. It relies on the virtual device model provided by the device simulation module, and defines and stores various possible SDH device fault scenarios by setting different fault parameters, fault types, fault occurrence time and duration on the model, providing device configuration simulation functions, supporting users to perform device configuration operations, and providing real-time feedback on configuration results. These fault scenarios need to be closely matched with the virtual device model to ensure that the device fault situation can be truly reproduced during the simulation process.

[0047] 2) Collaborative working relationship

[0048] ●Jointly build a simulation environment:

[0049] The device simulation module and the fault scenario definition module work together to build a complete simulation environment. In this environment, users can simulate the operation of real equipment under different fault scenarios to perform troubleshooting, maintenance training, performance evaluation and other operations. This collaborative working relationship enables the simulation system to more comprehensively reflect the operating status and fault characteristics of actual equipment.

[0050] Realize fault simulation and diagnosis process:

[0051] In the simulation environment, the device simulation module is responsible for simulating the normal operation of the device, while the fault scenario definition module is responsible for introducing various fault factors and triggering device failures. The device simulation module first starts and runs the virtual device model to simulate the normal operation of the device. Subsequently, the fault scenario definition module introduces corresponding fault factors on the virtual device model according to the preset fault scenario parameters to trigger device failures. Through the synergy of the two, users can perform fault simulation and diagnosis training by observing the behavioral characteristics and parameter changes of the virtual device under fault conditions. Through repeated practice and verification, users can gradually master the skills of equipment troubleshooting and maintenance.

[0052] 3) Summary of logical relationships

[0053] ●Basics and extensions:

[0054] The device simulation module provides the basic framework and virtual device model for the simulation system, which is the prerequisite for the normal operation of the simulation system; the fault scenario definition module expands and deepens on this basis, enriching the functions and application scenarios of the simulation system by defining various fault scenarios.

[0055] ● Mutual support and promotion:

[0056] The device simulation module and the fault scenario definition module support and promote each other. The device simulation module provides the necessary virtual device model for the fault scenario definition module; while the fault scenario definition module verifies and improves the accuracy and reliability of the device simulation model by defining fault scenarios. The close cooperation between the two enables the simulation system to more realistically reflect the operating status and fault characteristics of the actual equipment.

[0057] 2. “Fault injection module” and “fault simulation module”

[0058] There is a close logical relationship between the "fault simulation module" and the "fault injection module", which is mainly reflected in the following aspects:

[0059] 1) Functional complementation and synergy

[0060] Functions of the fault injection module:

[0061] The fault injection module is mainly responsible for artificially introducing various preset fault conditions in the test environment. These faults can be at the software level (such as memory leaks, dead loops, etc.) or at the hardware level (such as power fluctuations, signal interference, etc.). Through fault injection, various abnormal conditions that the system may encounter in actual operation can be simulated, such as optical cable breakage, loose interfaces, damaged equipment boards, software program errors, etc. These fault simulations can truly reflect the abnormal conditions of the equipment in actual operation.

[0062] ●Functions of fault simulation module:

[0063] The fault simulation module simulates the operating status and response of the system under these fault conditions based on the results of fault injection. Injection mechanism: allows teachers or the system to randomly or specifically inject faults in the simulation environment according to teaching needs to simulate real fault scenarios. Injection settings: After selecting the fault case, teachers need to set the specific parameters of fault injection in the fault injection module, such as fault type, injection time, fault level, etc. The setting of these parameters will directly affect the authenticity of the fault simulation and the teaching effect.

[0064] By using the faults introduced by the fault injection module, various possible failure scenarios of the system are simulated, and the performance of the system in these scenarios is observed.

[0065] Collaborative work:

[0066] a) Functional complementation:

[0067] These two modules complement each other in terms of function. The fault injection module is responsible for "creating" faults, while the fault simulation module is responsible for "observing" and "simulating" the impact of these faults on the system. Without fault injection, fault simulation is out of the question; similarly, without fault simulation, the effect of fault injection cannot be verified and evaluated.

[0068] b) Synergistic Effect:

[0069] They work together on the test target to form a complete fault simulation and testing process. The fault injection module provides the necessary fault sources for the fault simulation module, while the fault simulation module verifies the robustness and fault tolerance of the system by simulating fault scenarios. This synergy makes the testing process more comprehensive, in-depth and effective.

[0070] 2) Logical sequence and execution flow

[0071] Logical order:

[0072] a) Fault injection first:

[0073] The fault injection module is the first step in the entire fault simulation process. It is responsible for actively and purposefully introducing various preset fault conditions or abnormal situations in the test environment. During the test process, the fault injection module is usually used first to introduce faults into the system. These faults can be randomly selected or designed for specific scenarios. These faults can be simulations of software defects or simulations of hardware failures.

[0074] b) Fault simulation followed by:

[0075] After the fault is successfully injected, the fault simulation module takes over and continues the process. It simulates the operating behavior and response of the system or application under these fault conditions based on the fault conditions introduced by the fault injection module. The fault simulation module needs to be able to capture and accurately reflect the dynamic changes of the system after the fault is injected.

[0076] Next, the fault simulation module simulates the corresponding fault scenarios based on the introduced faults and observes the system's behavior under these scenarios.

[0077] ·Execution process:

[0078] Testers first determine the types of failures and scenarios that need to be tested.

[0079] Then, the fault injection module is used to inject corresponding faults into the system.

[0080] Then, the fault simulation module is started to simulate the operating status of the system under these fault conditions.

[0081] Finally, observe and record the system's response and performance to evaluate its reliability and stability.

[0082] 3) Relationship summary

[0083] Mutual dependence: The fault simulation module relies on the fault sources provided by the fault injection module to simulate fault scenarios; while the fault injection module requires the fault simulation module to verify whether the faults it injects are effective and how the system responds to these faults.

[0084] Common goal: The common goal of both is to improve the reliability and stability of the system, discover potential failures and defects through simulation and testing, and take corresponding measures to repair and improve them.

[0085] 3. “Fault diagnosis module” and “Fault repair module”

[0086] In the equipment fault diagnosis and repair system, the logical relationship between the "fault diagnosis module" and the "fault repair module" can be summarized as follows:

[0087] 1) Sequentiality and Dependency

[0088] Sequentiality:

[0089] The execution of the two modules follows a certain order. First, through the "fault location algorithm" of the "fault diagnosis module", a comprehensive fault detection and diagnosis is performed on the equipment or system to determine the type, location and possible cause of the fault. This is the premise and basis for any repair work.

[0090] After the fault diagnosis is completed, the "fault repair module" stage will be entered, and the corresponding repair plan will be formulated and the repair operation will be performed based on the diagnosis results.

[0091] ●Dependencies:

[0092] The "fault repair module" relies heavily on the output of the "fault diagnosis module". Only by accurately diagnosing the type and location of the fault can a targeted repair plan be formulated, thereby improving the success rate and efficiency of the repair.

[0093] 2) Functional complementation and synergy

[0094] ●Complementary functions:

[0095] The two modules complement each other in function and together constitute the core part of the equipment fault handling process. The "fault diagnosis" module is a virtual simulation teaching system for SDH communication equipment fault maintenance teaching, providing "fault diagnosis" tools and methods to guide students to conduct fault troubleshooting and analysis. The fault diagnosis module is responsible for "finding problems", while the fault repair module is responsible for "solving problems".

[0096] Through this functional complementarity, the system can quickly respond to and handle equipment failures, reducing downtime and production losses caused by failures.

[0097] Collaborative work:

[0098] In actual applications, these two modules often work together to form a closed-loop fault handling process. When a device fails, the fault diagnosis module is first started to detect the fault; then, the fault repair module is started to perform repair operations based on the diagnosis results; finally, the repair effect is evaluated and verified to ensure that the device resumes normal operation.

[0099] 3) Goal consistency

[0100] Whether it is a "fault diagnosis module" or a "fault repair module", their goal is to ensure the normal operation and reliability of equipment or systems. By accurately diagnosing faults and repairing them in a timely manner, the impact of faults on production operations can be reduced and the service life and performance of equipment can be improved.

[0101] 4. “Evaluation Feedback Module”:

[0102] The "Evaluation Feedback Module and Circular Learning" module evaluates the students' fault repair teaching through the "Teaching Evaluation Feedback Algorithm" and gives feedback. Students adjust their learning strategies based on the feedback, forming a closed loop of circular learning.

[0103] Embodiment 2:

[0104] A digital twin-based SDH communication equipment fault maintenance simulation teaching method includes the following steps:

[0105] S1. Equipment simulation: First, the teaching objectives need to be clearly defined: to ensure that students master the structure, working principle, troubleshooting and maintenance skills of SDH communication equipment, especially the troubleshooting of "SDH multiplex section protection switching failure".

[0106] Secondly, select the teaching content: combine the actual failure cases of SDH communication equipment to develop a detailed teaching plan and content.

[0107] Next, based on the basic parameters of the real equipment (including physical characteristics, working principles, parameter settings, etc.), a high-precision virtual SDH communication equipment model is constructed to simulate the normal operation of the SDH communication equipment; including the following aspects:

[0108] ·Choose appropriate virtual simulation software or platform: Use 3D modeling software (such as AutoCAD, SolidWorks, etc.) combined with simulation software (such as MATLAB / Simulink, OPNET, etc.). Support virtual simulation of SDH communication equipment, including equipment model, fault simulation, operation interface, etc. According to the actual SDH communication equipment structure, layout and connection method, establish the electrical characteristics and communication protocol model of the equipment model. Build a high-precision digital twin model. The model should include all equipment, fiber connections, interfaces and other details related to multiplex section protection.

[0109] Conduct a comprehensive survey of the physical structure, electrical characteristics, communication protocols and other data information of SDH communication equipment, integrate actual information such as equipment performance parameters, operating data, historical fault records into the digital twin model, and ensure that the model can truly reflect the actual status of the equipment.

[0110] Model refinement: Based on the 3D geometric model, further refine the model details, including the internal components, connection lines, indicator light status, etc. of the device, to ensure that the model can accurately reflect the actual status of the device.

[0111] Data response simulation: Realize data simulation between the digital twin model and the physical device (if available), including operating status, alarm information, configuration parameters, etc., so as to reflect the real response of the device in real time in the simulation environment.

[0112] Import SDH communication equipment model: According to the actual SDH communication equipment, build the corresponding equipment model in the virtual simulation teaching system, including key components such as multiplex section protection module, optical interface, cross connection, etc.

[0113] Specifically, the following steps are included:

[0114] S11. Data collection and integration: Collect fault status data of physical equipment, integrate performance parameters of physical equipment, and achieve a high degree of simulation of fault status response of physical equipment;

[0115] S12. Simulation model construction: Use three-dimensional modeling technology to construct a virtual SDH communication equipment model including the equipment appearance, internal structure, and connection relationship.

[0116] S2, fault scenario definition: setting different characteristic parameters (fault parameters, fault types, fault occurrence time and duration, etc.) on the virtual SDH communication equipment model to define various possible fault scenarios and obtain a fault test model;

[0117] S3. Fault injection: Introduce preset fault conditions (which can be software-level (such as memory leaks, dead loops, etc.) or hardware-level (such as power fluctuations, signal interference, etc.)) into the fault test model, including fiber disconnection, equipment failure, parameter configuration errors, etc. By modifying the parameters in the model or triggering specific events to simulate factors that may cause switching failures, such as fiber disconnection, node parameter setting errors, and equipment failures, simulate various abnormal situations that the system may encounter in actual operation; ensure that students can clearly understand the fault phenomenon, troubleshooting process, and maintenance operation methods.

[0118] S4, Fault simulation: Based on the injected fault conditions, simulate the operating state and response of the fault test model under these fault conditions;

[0119] S5, Fault diagnosis: According to the fault location algorithm, comprehensive fault detection and diagnosis are carried out to determine the type, location and possible cause of the fault, and output the diagnosis results;

[0120] S6, Fault repair: Based on the diagnosis results, the trainees formulate corresponding repair plans and perform repair operations;

[0121] S7. Evaluation and feedback: Use the teaching evaluation feedback algorithm to evaluate the students' fault repair solutions and repair operations (including operation accuracy, time efficiency, etc.) and provide feedback.

[0122] In this embodiment: S5, the "fault location algorithm" in fault diagnosis is further explained as follows: it adopts the "path tracing Dijkstra algorithm".

[0123] Dijkstra algorithm is an algorithm for finding the shortest path from a single source in a graph. Its main idea is based on greedy strategy and breadth-first search (BFS). In SDH equipment fault simulation diagnosis, Dijkstra algorithm can be used for fault search calculation, and the equipment topology structure can be abstracted into a graph in graph theory, where nodes represent SDH equipment boards and edges represent links between boards. To find the shortest (or optimal) path from the source node to the target node. After the fault is detected, the path tracing algorithm is used to determine the specific location where the fault occurs. The algorithm analyzes the SDH equipment structure and signal flow, combined with alarm information, gradually narrows the scope of the fault, and finally locates the specific board or link.

[0124] Dijkstra's algorithm is an algorithm for solving the single-source shortest path problem in a directed or undirected graph. It finds the shortest path by gradually building a shortest path tree from the source point to all other points.

[0125] The definition of Dijkstra's algorithm is:

[0126] 1) The shortest path from s to u relative to S: refers to the shortest path from s to u that only passes through vertices in S.

[0127] 2) dist[u]: the shortest path length from s to u relative to S

[0128] 3) short[u]: the length of the shortest path from s to u (the final solution of the algorithm)

[0129] 4)dist[u]≥short[u]

[0130] 5) Dijkstra algorithm adopts greedy algorithm mode. The algorithm process is to continuously expand the S set by calculating dist[u]. At the same time, dist[u] will be continuously optimized and improved until dist[u] = short[u], and put it into S. When all vertices are placed in the S set, the algorithm ends.

[0131] The schematic diagram of the algorithm principle is as follows Figure 1 shown.

[0132] In the fault simulation diagnosis of SDH equipment, the Dijkstra algorithm can be used to search the fault calculation route to locate the fault area.

[0133] The following are the implementation steps of Dijkstra algorithm. The algorithm flow chart is as follows: Figure 2 As shown:

[0134] 1. Initialization

[0135] · Set up the routing array: Create an array dist[] to store the shortest path estimates from the source to each node in the graph. Initially, the distance from the source to itself is set to 0 (dist[source] = 0), and the route from the source to all other nodes is set to infinity (dist[i] = ∞, for all i ≠ source).

[0136] Set the visited set: Create a set visited or array to record which nodes have been processed. Initially, the set is empty or all elements are initialized to false.

[0137] 2. Select the nearest unvisited node

[0138] In each iteration, select a node u from the unvisited nodes that is closest to the source and mark it as visited (i.e. set visited[u] to true or remove it from the unvisited set).

[0139] This step is usually implemented by traversing the dist[] array or using a priority queue (such as a binary heap) to optimize the search process.

[0140] 3. Update the routing of adjacent nodes

[0141] For each adjacent node v of node u, if the route to node v through node u (i.e., dist[u] + weight(u,v)) is less than the currently recorded route from the source to node v, dist[v], then update dist[v] to a smaller value and set the predecessor node of node v to u (this helps to trace back the shortest path later).

[0142] Repeat this step until all nodes have been visited or other termination conditions are met.

[0143] 4. Backtrack the shortest path

[0144] If you need to find the specific shortest path from a source node to a target node, you can do so by starting from the target node and tracing back to the source node along the links of the predecessor nodes.

[0145] In this embodiment, the “teaching evaluation feedback algorithm” is further described as follows:

[0146] The "teaching evaluation feedback algorithm" can use a variety of evaluation algorithm tools to ensure the comprehensiveness and accuracy of the evaluation. Among them, the "fuzzy comprehensive evaluation method is a method that uses fuzzy mathematics principles to conduct a comprehensive evaluation of complex systems through steps such as constructing a fuzzy evaluation set, determining membership functions, and calculating weights. It converts qualitative evaluation into quantitative evaluation based on the membership theory of fuzzy mathematics, thereby making an overall evaluation of things or objects that are constrained by multiple factors.

[0147] In the fuzzy comprehensive evaluation method, the fuzzy synthesis operation is the process of combining the weight vector with the membership matrix to obtain a comprehensive evaluation result vector.

[0148] The "fuzzy synthesis operator" used in this method is the "weighted average operator" (also called weighted average method) based on the Zadeh operator and its corresponding formula:

[0149] Weighted average = ∑(Wi*Xi) / ∑Wi.

[0150] Among them, Wi represents the weight of each vector, Xi represents the i-th vector, and ∑Wi is the sum of all weight items. This calculation method can convert the score of each item into a consistent weight, and then use their weighted average to represent the comprehensive performance of the item.

[0151] The basic flow chart of the "Fuzzy Comprehensive Evaluation" algorithm is as follows Figure 3 As shown:

[0152] 1) Constructing a fuzzy comprehensive evaluation index system

[0153] The selection of evaluation indicators should clarify the core content of the evaluation, that is, the teaching effect of virtual simulation SDH equipment fault maintenance. This includes students' understanding of the basic principles of SDH equipment, improvement of troubleshooting ability, mastery of maintenance skills, etc. According to the evaluation content, a complete set of evaluation indicator system is constructed.

[0154] 2) Setting factors and judgment sets

[0155] In the evaluation of the teaching effect of SDH equipment fault maintenance based on virtual simulation, the fuzzy comprehensive evaluation method involves constructing two sets, "factor set" and "judgment set", which can effectively quantify the teaching effect.

[0156] o "Factor set" is a collection of various attributes or influencing factors of the evaluation object (i.e., the teaching effect of virtual simulation SDH equipment fault maintenance). The factor set U can be expressed as:

[0157] U={U1,U2,…Un}

[0158] o "Judgement set" is a set of possible evaluation levels given when evaluating each factor in the "factor set". In fuzzy comprehensive evaluation, "Judgement set" is usually a set of ordered fuzzy language variables used to describe the performance of the evaluation object in different aspects. The judgment set can be expressed as:

[0159] V={V1,V2,…Vn}

[0160] These evaluation levels can be quantified according to actual conditions, for example, by using fuzzy numbers (such as triangular fuzzy numbers, trapezoidal fuzzy numbers, etc.) to represent the specific range and degree of membership of each evaluation level.

[0161] 3) Construct affiliation evaluation matrix

[0162] In the fuzzy comprehensive evaluation process, it is also necessary to determine a fuzzy relationship matrix (also called membership matrix) for each factor (element in U), which describes the degree to which the evaluation object belongs to each evaluation level in the evaluation set on each factor.

[0163] oThe membership function (single factor evaluation vector) is used to describe the fuzzy relationship between the evaluation factors and the evaluation levels.

[0164] oIn fuzzy comprehensive evaluation, fuzzy numbers are used to select appropriate membership function forms according to actual conditions (such as triangular fuzzy numbers, etc.) to represent the specific range and membership of each evaluation level. This method allows the evaluation level to have a certain degree of fuzziness, which is closer to the uncertainty in actual evaluation. Triangular fuzzy numbers are one of the simplest fuzzy numbers, which are defined by three parameters: the left endpoint (a), the middle point or the most likely point (R n ) and the right endpoint (b), denoted as (a, R, b). Where a≤R n ≤b. Corresponding to the "factor set" U = {U1, U2, ...Un} and the judgment set V = {V1, V2, ...Vn}, the membership function (single factor evaluation vector) is expressed as:

[0165] R n =1-n;

[0166] oThe affiliation evaluation matrix reflects the degree of affiliation of the evaluation object at each evaluation level.

[0167]

[0168] 4) Determine the weight of the evaluation factors

[0169] After the evaluation matrix R is formed, it can be combined with the weight vector W of the factor set U (usually determined by some method such as hierarchical analysis method, etc.) and fuzzy synthesis operators (such as weighted average type, main factor prominence type, etc.) to perform fuzzy comprehensive evaluation, and finally obtain the overall membership distribution of the evaluation object or a single evaluation result.

[0170] oThe weight reflects the importance of each evaluation factor in the comprehensive evaluation. Determine each evaluation factor based on the evaluation index system. These factors can be the students' mastery of knowledge points, proficiency of operating skills, accuracy of fault analysis, etc.

[0171] oUsing expert experience method, AHP hierarchical analysis method and other methods, according to the importance of each evaluation factor in the overall teaching effect, the corresponding weight is assigned. The weight reflects the relative importance of each factor in the comprehensive evaluation.

[0172] 5) Fuzzy comprehensive evaluation

[0173] o Perform a synthetic operation on the membership matrix and the weight vector to obtain a comprehensive evaluation value. First-level evaluation: Perform a synthetic operation on the membership matrix and the corresponding weight vector to obtain the first-level comprehensive evaluation value of the student in each evaluation dimension. Second-level evaluation (if the evaluation system has multiple layers): Use the first-level evaluation results as new evaluation factors, construct a new membership matrix, and perform further synthetic operations to obtain the second-level comprehensive evaluation value. This process can be carried out layer by layer until the final comprehensive evaluation result is obtained.

[0174] oThe comprehensive evaluation value reflects the overall quality of the evaluation object. Analyze the results of fuzzy comprehensive evaluation to understand the performance of students in each evaluation dimension. By analyzing the evaluation results, we can find the strengths and weaknesses in teaching. According to the evaluation results, put forward targeted teaching improvement suggestions. These suggestions can be used to strengthen training for students' weak links, or to optimize and adjust teaching methods and teaching content.

[0175] The “Fuzzy Comprehensive Evaluation” algorithm example is described as follows:

[0176] In order to better understand the evaluation of teaching effectiveness of SDH (Synchronous Digital Hierarchy) equipment fault maintenance based on virtual simulation, the "fuzzy comprehensive evaluation" algorithm is used as an effective tool to comprehensively evaluate the teaching quality and student learning outcomes. The following details the specific application and calculation of the "fuzzy comprehensive evaluation" algorithm in this method:

[0177] (I) Determine the evaluation content:

[0178] o Clearly define the evaluation objectives: evaluate the effectiveness of virtual simulation SDH equipment fault maintenance teaching, including students' mastery of theoretical knowledge, practical operation ability, fault detection and resolution ability, etc.

[0179] oConstruct an evaluation index system: According to the teaching objectives, construct an evaluation system containing multiple evaluation indicators. The system should be broken down into specific evaluation indicators, including knowledge mastery, skill operation, fault analysis, teamwork and other dimensions.

[0180] (II) Setting the factor set and judgment set:

[0181] In the scenario of "virtual simulation SDH equipment fault maintenance teaching", the "factor set" can include the following aspects:

[0182] 1. Knowledge mastery (U1): Assess whether students have fully mastered the key knowledge points and skills of SDH equipment fault maintenance through the virtual simulation system.

[0183] 2. Fault identification rate (U2): evaluates the speed at which students can identify SDH equipment faults in a virtual simulation environment.

[0184] 3. Troubleshooting rate (U3): evaluates the accuracy of students in repairing SDH equipment faults in a virtual simulation environment.

[0185] 4. Learning effect (U4): Evaluate the actual mastery and skill improvement of trainees after learning SDH equipment fault maintenance using the virtual simulation system.

[0186] 5. Teamwork (U5): Assess the teamwork of trainees in learning SDH equipment fault maintenance operations in a virtual simulation environment.

[0187] Therefore, the factor set U can be expressed as:

[0188] U={U1,U2,U3,U4,U5}

[0189] oIn the scenario of "virtual simulation SDH equipment fault maintenance teaching", for the evaluation of the virtual simulation SDH equipment fault maintenance teaching effect, the evaluation set V can be set as:

[0190] V={V1,V2,V3,V4,V5}={Excellent, Good, Average, Pass, Fail}

[0191] (III) Construct membership and evaluation matrix:

[0192] o According to the characteristics of SDH equipment fault maintenance teaching, select the appropriate membership function form. These functions are used to describe the fuzzy relationship between evaluation factors and evaluation levels. Convert the student's performance into the membership of the corresponding evaluation level. The membership function can be in the form of triangle, trapezoid, normal distribution, etc.

[0193] For the above judgment set V = {very poor, poor, average, good, very good}, we can assign a triangular fuzzy number to each evaluation level to represent its range and membership. For example: in the "learning effect (U4)", according to the actual mastery and skill improvement of students after using the virtual simulation system to learn SDH equipment fault maintenance, 5% are very poor, 10% are poor, 30% are average, 30% are good, and 25% are very good. Then the membership function (single factor evaluation vector) of "learning effect (U4)" is:

[0194] Membership function of learning effect R4 = (0.05, 0.10, 0.30, 0.30, 0.25)

[0195] oAccording to the membership function and the specific values ​​of the evaluation "factor set", data is collected through questionnaires, test scores, practical performance and other methods, and the membership matrix is ​​constructed by combining the "factor set" and the "judgment set". According to the membership function and the specific performance of students on each evaluation factor, a membership judgment matrix is ​​constructed. This matrix reflects the degree of student membership at each evaluation level.

[0196] Combined with the "factor set" of this example:

[0197] U={U1,U2,U3,U4,U5}={knowledge mastery, fault recognition rate, learning effect, teamwork, teamwork}

[0198] and the "judgment set":

[0199] V={V1,V2,V3,V4,V5}={Excellent, Good, Average, Pass, Fail}

[0200] Construct the membership evaluation matrix R of this example:

[0201]

[0202] (IV) Determine the weight:

[0203] oUse the analytic hierarchy process (AHP) or expert experience method to determine the weight of each evaluation index to reflect its importance in the teaching effect. In this example, the evaluation of the teaching effect of "SDH equipment fault maintenance based on virtual simulation", the application of the analytic hierarchy process (AHP) to form the weight vector W of the factor set U is a systematic and structured process.

[0204] (V) Fuzzy comprehensive evaluation:

[0205] oUse the fuzzy synthesis operator (such as Zadeh operator) to synthesize the weight vector and the membership matrix to obtain a comprehensive evaluation result vector.

[0206] Normalize the comprehensive evaluation result vector to obtain the membership degree of each evaluation level.

[0207] oBased on the normalized results, determine the final evaluation level or score according to the maximum membership principle or other principles.

[0208] oAnalyze the scores of each evaluation indicator, find out the advantages and disadvantages in teaching, and provide a basis for subsequent teaching improvements.

[0209] When using this embodiment for teaching, it is divided into the following steps:

[0210] 1. Theoretical explanation:

[0211] Through videos, PPT and other forms, students are introduced to the basic principles of SDH multiplex section protection, switching mechanism, and common fault types and causes.

[0212] Emphasize safety precautions and operating specifications that require attention during troubleshooting.

[0213] 2. Virtual simulation operation:

[0214] Self-diagnosis: Under the guidance of teachers, students conduct troubleshooting in a virtual simulation environment according to the steps in the teaching materials. Guide students to log in to the virtual simulation teaching system and enter the constructed digital twin model of SDH communication equipment. Gradually locate the cause of the fault by viewing alarm information, checking equipment status, adjusting parameter settings, etc.

[0215] Display fault phenomenon: By calling the fault simulation related to the fault mode library, the fault phenomenon of "SDH multiplex section protection switching failure" is simulated in the model, such as "the STM-N service configured with two-fiber unidirectional channel protection fails to automatically switch to the backup line when the main line fails, resulting in service interruption". And display the "APS_FAIL" alarm information, etc.

[0216] Guide students to troubleshoot by following the steps in the teaching materials:

[0217] a) First check whether the multiplexing segment node parameter settings are correct, adjust the parameters through the virtual operation interface and observe the results.

[0218] b) Use virtual tools (such as optical power meter, OTDR, etc.) to check the fiber connection status and simulate operations such as cleaning the pigtail head and replacing the optical fiber.

[0219] c) Check the device status and simulate operations such as viewing alarm information and restarting the device.

[0220] d) Verify whether the multiplex segment protection configuration is correct, simulate modifying the configuration and restarting the protection protocol.

[0221] During each operation, the system should provide real-time feedback and prompts to help students understand the impact of the operation on the model state.

[0222] Maintenance operations: Once the cause of the fault is determined, students perform maintenance operations in a virtual simulation environment, such as replacing faulty parts, adjusting parameter settings, etc.

[0223] 3. Interactive Q&A and discussion:

[0224] Set up interactive sessions during the virtual simulation process to encourage students to ask questions and discuss. Teachers can provide real-time answers and guidance based on students’ operations and questions.

[0225] After completing the troubleshooting using this embodiment, guide students to summarize the entire troubleshooting process, fault causes, treatment methods, and lessons learned. Evaluate students' performance in the troubleshooting process, including operation accuracy, time efficiency, etc., through the data recording function of the virtual simulation teaching system. Collect students' feedback to understand their satisfaction with the teaching methods, teaching content, and simulation teaching system and their suggestions for improvement. Based on the teaching effect evaluation and students' feedback, continuously optimize and improve the teaching methods, teaching content, and the functions and performance of the simulation teaching system.

[0226] Through the above steps, the troubleshooting teaching and operation training of "SDH multiplex section protection switching failure" can be effectively carried out to improve students' troubleshooting ability and maintenance operation skills.

[0227] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A simulation teaching method for fault maintenance of SDH communication equipment based on digital twins, characterized in that: The following steps are involved: S1. Equipment simulation: Based on the basic parameters of the real equipment, a virtual SDH communication equipment model is constructed to simulate the normal operation of the SDH communication equipment; S2, fault scenario definition: setting different characteristic parameters on the virtual SDH communication equipment model to define various possible fault scenarios and obtain a fault test model; S3, fault injection: introducing a preset fault condition into the fault test model to simulate various abnormal conditions that the system may encounter in actual operation; S4, Fault simulation: Based on the injected fault conditions, simulate the operating state and response of the fault test model under these fault conditions; S5, Fault diagnosis: According to the fault location algorithm, comprehensive fault detection and diagnosis are carried out to determine the type, location and possible cause of the fault, and output the diagnosis results; S6, Fault repair: Based on the diagnosis results, the trainees formulate corresponding repair plans and perform repair operations; S7. Evaluation and feedback: Use the teaching evaluation feedback algorithm to evaluate the students' fault repair solutions and repair operations, and provide feedback.

2. The SDH communication equipment fault maintenance simulation teaching method based on digital twin according to claim 1 is characterized in that: The device simulation in step S1 includes the following steps: S11. Data collection and integration: Collect fault status data of physical equipment, integrate performance parameters of physical equipment, and achieve a high degree of simulation of fault status response of physical equipment; S12. Simulation model construction: Use three-dimensional modeling technology to construct a virtual SDH communication equipment model including the equipment appearance, internal structure, and connection relationship.

3. The SDH communication equipment fault maintenance simulation teaching method based on digital twin according to claim 1 is characterized in that: The characteristic parameters in the fault scenario definition of S2 include fault parameters, fault type, fault occurrence time and duration.

4. The SDH communication equipment fault maintenance simulation teaching method based on digital twin according to claim 1 is characterized in that: The fault location algorithm in the fault diagnosis of S5 adopts the path tracing Dijkstra algorithm.

5. The SDH communication equipment fault maintenance simulation teaching method based on digital twin according to claim 1 is characterized in that: The teaching evaluation feedback algorithm in the evaluation feedback S7 adopts the fuzzy comprehensive evaluation method.

6. A system for executing the SDH communication equipment fault maintenance simulation teaching method based on digital twin as described in any one of claims 1 to 5, characterized in that: include: S1, equipment simulation module: according to the basic parameters of the real equipment, a virtual SDH communication equipment model is constructed to simulate the normal operation status of the SDH communication equipment; S2, fault scenario definition module: setting different characteristic parameters on the virtual SDH communication device model to define various possible fault scenarios and obtain a fault test model; S3, fault injection module: introduces preset fault conditions into the fault test model to simulate various abnormal conditions that the system may encounter in actual operation; S4, fault simulation module: based on the injected fault conditions, simulate the operating state and response of the fault test model under these fault conditions; S5, fault diagnosis module: according to the fault location algorithm, conduct comprehensive fault detection and diagnosis, determine the type, location and possible cause of the fault, and output the diagnosis result; S6, Fault repair module: Based on the diagnosis results, students formulate corresponding repair plans and perform repair operations; S7, Evaluation and feedback module: Use the teaching evaluation and feedback algorithm to evaluate the students' fault repair solutions and repair operations, and provide feedback.

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