Dual-protocol integration system and method for communication equipment maintenance and detection equipment and knowledge base

Abstract

The invention discloses a dual-protocol integration system and method for communication equipment maintenance and detection equipment and a knowledge base, and belongs to the technical field of communication equipment maintenance and intelligent diagnosis. Comprising a detection equipment dual-protocol access layer, a data fusion layer, a customized knowledge base layer and an inference engine layer which are in communication connection in sequence, the detection equipment dual-protocol access layer is provided with a dual-protocol adaptive interface module and an equipment verification unit which are in communication connection with each other, the dual-protocol adaptive interface module supports cooperative work of a Socket protocol and a VNC protocol, and dual requirements of real-time transmission of detection data and remote control of equipment are met; according to the communication equipment maintenance and detection equipment and knowledge base dual-protocol integration system and method, the data transmission delay is less than or equal to 30 ms, the remote control response delay is less than or equal to 100 ms, the fault positioning accuracy is greater than or equal to 96%, the knowledge base can absorb newly added fault cases within 1-3 days, and the communication equipment maintenance efficiency and adaptability are greatly improved.

Description

A dual-protocol integration system and method for communication equipment repair and testing equipment and knowledge base Technical Field

[0001] This invention specifically relates to a dual-protocol integrated system and method for communication equipment repair and testing equipment and knowledge base, belonging to the field of communication equipment repair and intelligent diagnostic technology. Background Technology

[0002] In the current process of repairing communication equipment, the integration of testing equipment and maintenance knowledge base suffers from technical pain points such as single protocol compatibility and fragmented functions. On the one hand, existing integration solutions mostly use a single communication protocol for data transmission, which cannot simultaneously meet the dual needs of real-time interaction of testing data and remote control of equipment. This forces maintenance personnel to switch between multiple systems, resulting in low efficiency. On the other hand, the data formats output by testing equipment (including binary logs, custom fault codes, real-time parameters, etc.) lack a unified parsing standard. Existing systems cannot directly interface with different types of testing equipment, requiring manual data conversion and filtering, which is prone to human error and has high adaptation costs. In addition, existing maintenance knowledge bases are not customized for the fault propagation patterns and parameter characteristics of testing equipment. The knowledge organization lacks structured logic and relies only on single fault codes for matching, making it impossible to locate the root cause of the fault by comprehensively analyzing multi-dimensional testing data. At the same time, knowledge base updates rely on manual input of maintenance cases, resulting in long update cycles and an inability to quickly adapt to new fault types brought about by communication network upgrades. Therefore, there is an urgent need for a knowledge base system and method that adopts dual-protocol collaborative integration and adapts to the data characteristics of testing equipment, in order to solve the technical problems of single protocol function, inefficient data docking, insufficient accuracy of fault diagnosis, and lagging knowledge updates in the existing technology. Summary of the Invention

[0003] To address the aforementioned issues, this invention proposes a dual-protocol integration system and method for communication equipment repair and testing equipment and a knowledge base. This system solves the problems of existing integration schemes using a single protocol, which cannot simultaneously meet the requirements of real-time transmission of testing data and remote equipment control; it also addresses the issues of diverse data formats in testing equipment, the lack of a unified parsing mechanism leading to low efficiency and high adaptation costs in connecting with the knowledge base; it resolves the problems of disordered knowledge organization in existing knowledge bases, the failure to model fault patterns in testing equipment, and insufficient accuracy in fault diagnosis; and it addresses the issues of knowledge base updates relying on manual intervention, the inability to quickly absorb new repair cases and testing data, and poor adaptability.

[0004] The present invention relates to a dual-protocol integration system for communication equipment repair and testing equipment and a knowledge base, comprising a dual-protocol access layer for testing equipment, a data fusion layer, a customized knowledge base layer, and an inference engine layer connected in sequence. The dual-protocol access layer for testing equipment is equipped with a dual-protocol adaptation interface module and a device verification unit that are connected in mutual communication. The dual-protocol adaptation interface module supports the collaborative operation of Socket protocol and VNC protocol, and the device verification unit is used to verify the device communication identifier and protocol compatibility.

[0005] Furthermore, the Socket protocol is used for real-time data communication between the detection device and the system. The data types include detection logs, fault codes, and real-time operating parameters, and the data transmission delay is ≤30ms. The VNC protocol is used for remote control of the detection device by maintenance personnel. The control functions include parameter configuration, detection command issuance, and device status adjustment, and the remote control response delay is ≤100ms.

[0006] Furthermore, the data fusion layer includes a data parsing engine, a feature extraction module, and a three-dimensional correlation modeling unit; the data parsing engine presets parsing rules for multiple types of detection data, and automatically identifies binary logs, text-type fault codes, and numerical parameters and converts them into structured feature vectors; the three-dimensional correlation modeling unit constructs a three-dimensional correlation model of fault codes, detection parameters, and equipment symptoms.

[0007] Furthermore, the customized knowledge base layer includes a structured knowledge graph storage unit, a knowledge update engine, and a conflict detection module; the knowledge graph storage unit constructs a structured knowledge graph based on the hardware hierarchy of the communication detection equipment and the fault propagation law, and the knowledge nodes cover fault types, fault causes, maintenance plans, and detection standards; the conflict detection module identifies knowledge conflicts and redundancies based on the semantic understanding ability of a large language model.

[0008] A dual-protocol integration method for communication equipment repair and testing equipment and a knowledge base is disclosed. This method includes the following steps: Step 1: Construction and management of a customized knowledge base for communication equipment repair; Step 2: Dual-protocol access and data acquisition, establishing a connection between the system and the testing equipment and acquiring data, ensuring data acquisition integrity ≥99.9%; Step 3: Data parsing and feature extraction, parsing multi-format testing data and filtering abnormal parameters and corresponding equipment symptoms; Step 4: Association matching, matching the fault code-abnormal parameter-equipment symptom model with the knowledge graph, and filtering candidate fault causes with a confidence level ≥90%; Step 5: Dynamic updating and conflict detection of the knowledge base.

[0009] Furthermore, in step 2, the Socket protocol automatically collects detection logs, fault codes, and real-time operating parameters, including channel attenuation, signal-to-noise ratio, and bit error rate; the VNC protocol establishes a remote control channel to support maintenance personnel in remotely operating the detection equipment.

[0010] Furthermore, in step 5, the knowledge update engine receives maintenance execution result data through a closed-loop feedback mechanism and automatically updates the node associations and weights of the knowledge graph; the conflict detection module traverses the knowledge base every 1-7 days, outputs optimization suggestions, and completes the knowledge base optimization after manual review.

[0011] Further, the specific working process of step 1 is as follows: Step A: Collect communication equipment repair manuals, fault case databases, and industry testing standards; extract knowledge entities through entity recognition algorithms optimized based on BERT pre-trained models; and construct an initial structured knowledge graph. Step B: Receive repair data through a closed-loop feedback mechanism; and automatically update the knowledge graph node information and association weights. Step C: Identify logical contradictions and redundant information in the knowledge base; output optimization suggestions; and complete the optimization.

[0012] Furthermore, in step A, the hardware hierarchy is “host-functional board-core module-component”, and the relationship between knowledge entities is constructed based on the fault propagation law, including the association path of “core module failure → parameter abnormality → fault code trigger”.

[0013] Furthermore, in step C, the logical contradiction includes the same fault code corresponding to different fault causes and having no applicable conditions. The optimization method is to supplement applicable conditions or delete redundant entries.

[0014] Compared with the prior art, the dual-protocol integrated system and method of communication equipment repair and testing equipment and knowledge base of the present invention has the following advantages: 1. Dual-protocol collaborative integration, complementary and efficient functions: Through the collaborative work of Socket protocol and VNC protocol, real-time transmission of test data and remote control of equipment can be realized at the same time without switching multiple systems, improving the efficiency of repair operation by 85%, with data transmission delay ≤30ms and remote control response delay ≤100ms.

[0015] 2. Strong data adaptability and high integration efficiency: The dedicated data parsing engine supports automatic parsing of multi-format detection data without manual conversion, achieving 100% data parsing accuracy and reducing equipment adaptation costs by 70%.

[0016] 3. High accuracy in fault diagnosis: Based on the three-dimensional correlation model of "fault code-detection parameter-equipment symptoms" and structured knowledge graph, the fault location accuracy is improved to over 96%, and the root cause fault identification rate reaches 98%.

[0017] 4. Self-evolving knowledge base with strong adaptability: Through a closed-loop feedback automatic update mechanism, the knowledge base can absorb new fault cases and detection features within 1-3 days, eliminating the need for large-scale manual data entry and quickly adapting to maintenance needs after communication network upgrades.

[0018] 5. Enhanced operational flexibility: Supports remote control of testing equipment by maintenance personnel, and real-time adjustment of testing parameters based on maintenance solutions output from the knowledge base, adapting to various scenarios such as remote maintenance and collaborative diagnosis of complex faults. Attached Figure Description

[0019] Figure 1 is a schematic diagram of the overall module connection of the dual-protocol integrated system of communication equipment repair and testing equipment and knowledge base of the present invention.

[0020] Figure 2 is a schematic diagram of the specific connection structure of the dual-protocol integrated system of communication equipment repair and testing equipment and knowledge base of the present invention.

[0021] Figure 3 is a schematic diagram of the dual-protocol integration method of the communication equipment repair and testing equipment and knowledge base of the present invention.

[0022] Figure 4 is a schematic diagram of the construction and management process of the customized knowledge base for communication equipment maintenance of the present invention. Detailed Implementation

[0023] As shown in Figures 1 and 2, the dual-protocol integration system for communication equipment repair and testing equipment and its knowledge base includes a dual-protocol access layer for testing equipment, a data fusion layer, a customized knowledge base layer, and an inference engine layer, all connected in sequence. The dual-protocol access layer deploys a dual-protocol adaptation interface module and a device verification unit. The dual-protocol adaptation interface module supports the collaborative operation of Socket and VNC protocols. The Socket protocol is used for real-time data communication between the testing equipment and the system (including testing logs, fault codes, real-time operating parameters, etc.), while the VNC protocol is used for remote control of the testing equipment by maintenance personnel (including parameter configuration, testing command issuance, equipment status adjustment, etc.). The device verification unit verifies the device communication identifier and protocol compatibility to ensure legitimate device access. The Socket protocol data transmission latency is ≤30ms, and the VNC protocol remote control response latency is ≤100ms. The data fusion layer includes a dedicated data parsing engine, a feature extraction module, and a 3D correlation modeling unit. The dedicated data parsing engine presets parsing rules for multiple types of testing data, automatically recognizing data formats such as binary logs, text-based fault codes, and numerical parameters, converting unstructured data into structured feature vectors, and... The system maps custom fault codes to standardized descriptions. A feature extraction module, based on a communication equipment fault feature library, extracts abnormal parameters, fault codes, and equipment operating symptoms from the detection data. A 3D association modeling unit constructs a 3D association model of "fault code - detection parameter - equipment symptoms," achieving multi-dimensional and accurate mapping between detection data and the knowledge base. The customized knowledge base layer includes a structured knowledge graph storage unit, a knowledge update engine, and a conflict detection module. The knowledge graph storage unit constructs a structured knowledge graph based on the hardware hierarchy of the communication detection equipment (host - function board - core module - components) and fault propagation patterns. Knowledge nodes cover core information such as fault type, fault cause, maintenance plan, and detection standards. The knowledge update engine receives maintenance execution result data through a closed-loop feedback mechanism and automatically updates the node relationships and weights of the knowledge graph. The conflict detection module, based on the semantic understanding capabilities of a large language model, identifies contradictory or redundant knowledge entries in the knowledge base and outputs optimization suggestions. The reasoning engine layer calls the structured knowledge of the customized knowledge base layer and, combined with the processing results of the data fusion layer, performs fault diagnosis and maintenance plan generation. It also supports synchronizing maintenance guidance instructions to the detection equipment via the VNC protocol.

[0024] As shown in Figures 3 and 4, a dual-protocol integration method for communication equipment repair and testing equipment and a knowledge base includes the following steps: Step 1: Construction and management of a customized knowledge base for communication equipment repair, specifically as follows: Step 1.1: Initial construction of the knowledge graph; collecting communication equipment repair manuals, fault case databases, and industry testing standards; extracting knowledge entities (such as "core module fault", "capacitor aging", "component replacement", etc.) through entity recognition algorithms (optimized based on BERT pre-trained models); constructing the association relationships between knowledge entities based on the hardware hierarchy and fault propagation rules of the communication testing equipment (such as "core module fault → abnormal voltage fluctuation → fault"). Step 1.2: Dynamic update of the knowledge graph; through a closed-loop feedback mechanism, maintenance execution result data is received, and the knowledge update engine automatically updates the node information (such as adding new fault type nodes) and association weights (such as strengthening the feature association strength of high-frequency faults) of the knowledge graph; Step 1.3: Knowledge base conflict detection and optimization; the conflict detection module, based on the semantic understanding capability of the large language model, identifies logical contradictions (such as the same fault code corresponding to different fault causes and having no applicable conditions) and redundant information in the knowledge base, outputs a conflict list and optimization suggestions, and after manual review, adds applicable conditions or deletes redundant entries to complete the knowledge base optimization.

[0025] Step 2: Dual-protocol access and data acquisition; A connection is established between the system and the testing equipment through a dual-protocol adapter interface module. The Socket protocol automatically acquires the testing logs, fault codes, and real-time operating parameters (such as channel attenuation, signal-to-noise ratio, bit error rate, etc.) output by the testing equipment. The VNC protocol establishes a remote control channel, supporting remote operation of the testing equipment by maintenance personnel. The equipment verification unit verifies the equipment communication identifier and protocol compatibility, ensuring data acquisition integrity ≥99.9%. Step 3: Data parsing and feature extraction; A dedicated data parsing engine parses multi-format testing data according to preset rules, converting binary logs into structured parameters and mapping custom fault codes to standardized descriptions. The feature extraction module compares the communication equipment's testing standards to filter abnormal parameters (such as...). Step 4: Matching the detection data with the knowledge base; The 3D association modeling unit matches the extracted "fault code-abnormal parameter-equipment symptoms" with the knowledge graph nodes, calculates the matching confidence, and filters out candidate fault causes with a confidence of ≥90%; Step 5: Dynamic updating of the knowledge base and conflict detection; After the maintenance personnel complete the maintenance, they feed back the actual fault cause, effective maintenance steps, and newly added detection features to the system; The knowledge update engine automatically adds the new information to the knowledge graph and updates the node association weights; The conflict detection module periodically (can be set from 1 to 7 days) traverses the knowledge base, identifies logically contradictory or redundant knowledge entries, outputs optimization suggestions, and completes the knowledge base optimization after manual review.

[0026] Example 1: Dual Protocol Integration and Data Processing: 1. Device Access: The communication equipment repair and testing equipment is connected to the system through the dual protocol adapter interface module. After the device verification unit verifies the device communication identifier and protocol compatibility, a stable connection is established. The test data acquisition is started through the Socket protocol, and a remote control channel is established through the VNC protocol.

[0027] 2. Data Acquisition: Acquire binary detection logs, custom fault codes "ERR-XX", and real-time parameters (channel attenuation: 28dB, signal-to-noise ratio: 22dB, bit error rate: 3.5×10⁻⁶) from the device output via Socket protocol. -5 Maintenance personnel can remotely adjust the equipment's testing accuracy parameters and issue secondary testing commands via the VNC protocol.

[0028] 3. Data Parsing and Feature Extraction: A dedicated data parsing engine parses binary logs, converting them into structured parameters, mapping "ERR-XX" to the standardized description "signal-to-noise ratio too low"; the feature extraction module compares the data against detection standards (channel attenuation ≤30dB, signal-to-noise ratio ≥25dB, bit error rate ≤10%). -6 ), Filtering for abnormal features: signal-to-noise ratio 22dB (abnormal), bit error rate 3.5×10 -5 (Abnormality), corresponding to the device symptom "Decreased channel transmission stability".

[0029] 4. Association Matching: The 3D association modeling unit matches "ERR-XX-Signal-Noise Ratio 22dB-Decreased Transmission Stability" with the knowledge graph, and hits the association path "ERR-XX→Abnormal Signal-Noise Ratio→Fault in Core Module Signal Processing Unit", with a matching confidence level of 94%.

[0030] Example 2: Knowledge Base Construction and Dynamic Update: 1. Knowledge Graph Initialization: Collect communication equipment repair manuals, 500+ fault cases, and industry testing standards (YD / T2866-2021), extract knowledge entities such as "core module signal processing unit", "cold solder joint", and "hot air gun repair soldering", and build the association relationship based on the hardware level "testing equipment host - function board - core module - signal processing unit" to form an initial knowledge graph.

[0031] 2. Repair Feedback and Knowledge Update: Repair personnel remotely reproduce the fault via VNC protocol. After completing the repair according to the repair plan output by the knowledge base (hot air gun repair of the signal processing unit), they provide feedback on the actual fault cause "poor soldering of the signal processing unit pins" and the newly added detection feature "unit power supply voltage fluctuation ±0.2V". The knowledge update engine automatically adds this new feature to the knowledge graph and establishes a correlation with "ERR-XX" and "abnormal signal-to-noise ratio", increasing the correlation weight from 0.94 to 0.97.

[0032] 3. Conflict Detection: When the conflict detection module traversed the knowledge base, it found that one entry recorded "ERR-YY corresponds to excessive channel attenuation" and another entry recorded "ERR-YY corresponds to insufficient power supply to the core module", without distinguishing the applicable conditions. After manual review, the applicable conditions were added: "When the channel attenuation is >28dB, the corresponding channel attenuation exceeds the standard; when the power supply voltage is <5V, the corresponding core module has insufficient power supply", thus completing the knowledge base optimization.

[0033] The above embodiments are merely preferred embodiments of the present invention. Therefore, all equivalent changes or modifications made to the structure, features and principles described in the claims of the present invention are included within the scope of the present invention.

Claims

1. A dual-protocol integrated system for communication equipment repair and testing equipment and a knowledge base, characterized in that: The system includes a detection device dual-protocol access layer, a data fusion layer, a customized knowledge base layer, and an inference engine layer that are connected in sequence. The detection device dual-protocol access layer is equipped with a dual-protocol adaptation interface module and a device verification unit that are connected in sequence. The dual-protocol adaptation interface module supports the collaborative operation of Socket protocol and VNC protocol. The device verification unit is used to verify the device communication identifier and protocol compatibility.

2. The dual-protocol integrated system of communication equipment repair and testing equipment and knowledge base according to claim 1, characterized in that, The Socket protocol is used for real-time data communication between the detection device and the system. Data types include detection logs, fault codes, and real-time operating parameters, and the data transmission delay is ≤30ms. The VNC protocol is used for remote control of the detection device by maintenance personnel. Control functions include parameter configuration, detection command issuance, and device status adjustment, and the remote control response delay is ≤100ms.

3. The dual-protocol integrated system of communication equipment repair and testing equipment and knowledge base according to claim 1, characterized in that, The data fusion layer includes a data parsing engine, a feature extraction module, and a 3D correlation modeling unit; the data parsing engine presets parsing rules for multiple types of detection data, and automatically identifies binary logs, text-based fault codes, and numerical parameters and converts them into structured feature vectors; The three-dimensional correlation modeling unit constructs a three-dimensional correlation model of fault codes, detection parameters, and equipment symptoms.

4. The dual-protocol integrated system of communication equipment repair and testing equipment and knowledge base according to claim 1, characterized in that, The customized knowledge base layer includes a structured knowledge graph storage unit, a knowledge update engine, and a conflict detection module. The knowledge graph storage unit constructs a structured knowledge graph based on the hardware hierarchy of the communication detection equipment and the fault propagation rules. The knowledge nodes cover fault types, fault causes, maintenance plans, and detection standards. The conflict detection module identifies knowledge conflicts and redundancies based on the semantic understanding capabilities of a large language model.

5. A method for integrating a communication equipment repair and testing device with a knowledge base using a dual-protocol system as described in any one of claims 1 to 4, characterized in that, The method The process includes the following steps: Step 1: Construction and management of a customized knowledge base for communication equipment repair; Step 2: Dual-protocol access and data acquisition, establishing a connection between the system and the testing equipment and acquiring data, ensuring data acquisition integrity ≥99.9%; Step 3: Data parsing and feature extraction, parsing multi-format testing data and filtering abnormal parameters and corresponding equipment symptoms; Step 4: Association matching, matching the fault code-abnormal parameter-equipment symptom model with the knowledge graph, and filtering candidate fault causes with a confidence level ≥90%; Step 5: Dynamic updating of the knowledge base and conflict detection.

6. The dual-protocol integration method for communication equipment repair and testing equipment and knowledge base according to claim 5, characterized in that, In step 2, the Socket protocol automatically collects detection logs, fault codes, and real-time operating parameters, including channel attenuation, signal-to-noise ratio, and bit error rate; the VNC protocol establishes a remote control channel to support maintenance personnel in remotely operating the detection equipment.

7. The dual-protocol integration method for communication equipment repair and testing equipment and knowledge base according to claim 5, characterized in that, In step 5, the knowledge update engine receives maintenance execution result data through a closed-loop feedback mechanism and automatically updates the node associations and weights of the knowledge graph. The conflict detection module traverses the knowledge base every 1-7 days, outputs optimization suggestions, and completes the knowledge base optimization after manual review.

8. The dual-protocol integration method for communication equipment repair and testing equipment and knowledge base according to claim 5, characterized in that, The specific working process of step 1 is as follows: Step A: Collect communication equipment repair manuals, fault case databases, and industry testing standards; extract knowledge entities through entity recognition algorithms optimized based on BERT pre-trained models; and construct an initial structured knowledge graph. Step B: Receive maintenance data through a closed-loop feedback mechanism and automatically update the knowledge graph node information and association weights; Step C: Identify logical contradictions and redundant information in the knowledge base, output optimization suggestions, and complete the optimization.

9. The dual-protocol integration method for communication equipment repair and testing equipment and knowledge base according to claim 8, characterized in that, In step A, the hardware hierarchy is "host-functional board-core module-component". The relationship between knowledge entities is constructed based on the fault propagation law, including the association path of "core module failure → parameter abnormality → fault code trigger".

10. The dual-protocol integration method for communication equipment repair and testing equipment and knowledge base according to claim 8, characterized in that, In step C, the logical contradiction includes the same fault code corresponding to different fault causes and having no applicable conditions. The optimization method is to supplement applicable conditions or delete redundant entries.

Images