Fault positioning method, device and system for information communication system

Abstract

The invention discloses a fault positioning method, device and system for an information communication system. According to the method, firstly, operation data of an information communication system are collected, and on the basis, various algorithms in a fault diagnosis algorithm library are applied to analyze the data, so that system faults are accurately diagnosed. The fault diagnosis algorithms are obtained through continuous learning and optimization of a self-learning module, and can adapt to system changes and improve diagnosis accuracy. According to a diagnosis result, the system accurately matches a fault position, and effective positioning of the fault is realized. The fault positioning method not only improves the diagnosis efficiency and quality, but also ensures the high reliability and stability of the information communication system, greatly optimizes the operation and maintenance process of the system, ensures the continuity and safety of the communication service, and greatly improves the reliability and reliability of the information communication system through the implementation of the method. The method is of great significance in guaranteeing healthy operation of an information communication system and improving service quality.

Description

Technical Field

[0001] The present invention belongs to the field of network communication technology, and in particular relates to a fault locating method, device and system for an information communication system. Background Art

[0002] Communication and information systems are the core pillars of the information society and an important part of modern high-tech. They are like the nervous system and lifeblood of the national economy. The main research objects of this discipline include information acquisition, transmission and exchange, information network, information processing and information control, covering a wide range of fields such as telecommunications, broadcasting, television, radar, sonar, navigation, remote control and telemetry, remote sensing, electronic countermeasures, measurement and control, and involving many information systems in various military and national economic sectors.

[0003] In modern information and communication systems, fault location has become increasingly difficult due to the complexity of the network and the diversity of equipment. Traditional information and communication system fault location methods usually rely on manual experience, which is not only time-consuming and inefficient, but also increasingly challenging and complex as the scale of the network expands. This not only reduces the efficiency and accuracy of fault location, but also affects the stability and reliability of the entire information and communication system, making it difficult to meet the needs of long-term stable operation. Summary of the invention

[0004] The technical problem to be solved by the present invention is to address the above-mentioned deficiencies in the prior art and propose a fault location method, device and system for an information communication system. The method can efficiently and accurately locate the fault of the information communication system, thereby improving the efficiency and quality of fault diagnosis and ensuring the reliability and stability of the system.

[0005] In a first aspect, the present invention provides a fault location method for an information communication system, the method comprising the following steps:

[0006] Step S1: Acquire operation information data of the information communication system;

[0007] Step S2: using the fault diagnosis algorithm in the diagnosis algorithm library to perform fault analysis on the operation information data of the information communication system to obtain the fault result of the information communication system;

[0008] Wherein, the fault diagnosis algorithm is obtained by continuous learning and optimization through a self-learning module;

[0009] Step S3: Match the fault location according to the fault result to complete the fault location for the information communication system.

[0010] Furthermore, the step S1 specifically includes the following steps:

[0011] Step S11: monitor network traffic in real time and collect network traffic data through a network probe; and extract stored log information from a log server to obtain log data of an information communication system; and obtain device status information through a device interface;

[0012] The network traffic data includes network data packets, traffic patterns, and bandwidth usage; the device status information includes the device's CPU usage, memory status, port status, and connection status;

[0013] Step S12: Integrate the network traffic data, the log data and the device status information to obtain operation information data of the information communication system.

[0014] Further, after step S1 and before step S2, the method further includes step K;

[0015] Step K: preprocessing the operation information data of the information communication system;

[0016] The step K specifically comprises the following steps:

[0017] Step K1: Cleaning the operation information data of the information communication system to obtain cleaned operation information data;

[0018] Wherein, the data cleaning includes identifying and deleting random noise in the operation information data, and removing detection abnormal values ​​in the operation information data;

[0019] Step K2: extracting features from the cleaned operation information data to obtain extracted feature information;

[0020] Step K3: storing the extracted characteristic information to complete the preprocessing of the operation information of the information communication system.

[0021] Further, after step S3, the method further includes step S4;

[0022] Step S4: inputting the fault result and the fault location into the fault diagnosis algorithm in the diagnosis algorithm library to form a new fault diagnosis algorithm.

[0023] Further, after step S3, the method further includes step S5;

[0024] Step S5: Issue a fault alarm according to the fault result, display the fault handling process, and record the entire process of fault handling.

[0025] Furthermore, before step S2, the method further includes:

[0026] Step S0: construct a diagnostic algorithm library;

[0027] The step S0 specifically includes the following steps:

[0028] Obtain historical fault data of information and communication systems;

[0029] Use clustering algorithm to classify the historical fault data of information communication system and obtain different fault classification data;

[0030] According to the fault classification data, the original fault diagnosis model is trained to obtain a fault diagnosis model, wherein the fault diagnosis model includes a fault cause and a diagnosis strategy;

[0031] Among them, different information communication system faults correspond to different original fault diagnosis models; the original fault diagnosis model is constructed based on the selected machine learning model or deep learning model.

[0032] In a second aspect, the present invention provides a fault location device for an information communication system, the device comprising:

[0033] An acquisition unit, used to acquire operation information data of the information communication system;

[0034] An analysis unit connected to the acquisition unit, used to perform fault analysis on the operation information data of the information communication system using a fault diagnosis algorithm in a diagnosis algorithm library to obtain a fault result of the information communication system;

[0035] Wherein, the fault diagnosis algorithm is obtained by continuous learning and optimization through a self-learning module;

[0036] A matching unit is connected to the analyzing unit and is used to match the fault location according to the fault result to complete the fault location for the information communication system.

[0037] Furthermore, the acquisition unit includes:

[0038] A first acquisition module is used to monitor network traffic in real time and collect network traffic data through a network probe;

[0039] A second acquisition module is used to extract the stored log information from the log server to obtain the log data of the information communication system;

[0040] A third acquisition module is used to obtain device status information through a device interface;

[0041] The network traffic data includes network data packets, traffic patterns, and bandwidth usage; the device status information includes the device's CPU usage, memory status, port status, and connection status;

[0042] An integration module is connected to the first acquisition module, the second acquisition module and the third acquisition module, and is used to integrate the network flow data, the log data and the device status information to obtain operation information data of the information communication system.

[0043] Furthermore, the device also includes a construction unit;

[0044] The building block comprises:

[0045] An acquisition subunit, used for acquiring historical fault data of the information communication system;

[0046] A classification subunit, connected to the acquisition subunit, for classifying the historical fault data of the information communication system using a clustering algorithm to obtain different fault classification data;

[0047] A training subunit, connected to the classification subunit, for training the original fault diagnosis model according to the fault classification data to obtain a fault diagnosis model, wherein the fault diagnosis model includes a fault cause and a diagnosis strategy;

[0048] Among them, different information communication system faults correspond to different original fault diagnosis models; the original fault diagnosis model is constructed based on the selected machine learning model or deep learning model.

[0049] In a third aspect, the present invention provides a fault location system for an information communication system, the system comprising:

[0050] A fault location module, used to execute the fault location method for the information communication system as described in the first aspect, and obtain fault location data whose fault result matches the fault location;

[0051] A data storage module, which is in communication connection with the fault location module and is used to store fault location data of the information communication system;

[0052] A user interaction module is connected to the data storage module for displaying the fault location data in the data storage module.

[0053] The present invention comprehensively acquires system operation information data, combines it with continuously optimized fault diagnosis algorithms for intelligent analysis, and uses a self-learning mechanism to adapt to new fault modes, so as to quickly identify and match fault locations, thereby efficiently and accurately locating faults in information communication systems. The automation of this process greatly reduces the reliance on manual intervention, improves the accuracy and efficiency of fault location, and thus ensures the reliability and stability of the system. The specific beneficial effects are as follows:

[0054] 1. By using historical fault data, the present invention can continuously optimize the diagnostic algorithm and processing scheme, thereby improving the accuracy and efficiency of future fault processing.

[0055] 2. Through the fault diagnosis algorithm, the present invention significantly improves the accuracy of fault identification and reduces the occurrence of missed alarms and false alarms, thereby ensuring that faults can be handled in a timely and effective manner.

[0056] 3. The present invention can identify potential failures and support preventive maintenance through real-time monitoring and data analysis, which helps to reduce the failure rate of equipment.

[0057] 4. By adopting an automated fault diagnosis and processing process, the present invention reduces the reliance on manual intervention, reduces operation and maintenance costs, and mitigates the economic losses caused by faults.

[0058] 5. The present invention increases user satisfaction and trust through rapid and accurate fault handling, ensuring that users can use information communication services stably. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 A schematic diagram of a fault location process for an information communication system in an embodiment of the present invention;

[0060] Figure 2 It is a schematic diagram of an overall framework for fault location in an information communication system in an embodiment of the present invention;

[0061] Figure 3 A schematic diagram of a fault location method for an information communication system in an embodiment of the present invention;

[0062] Figure 4 is a schematic diagram of a fault location device for an information communication system in an embodiment of the present invention;

[0063] Among them, the figure marks are: 10, acquisition unit, 20, analysis unit, 30, matching unit. DETAILED DESCRIPTION

[0064] In order to enable those skilled in the art to better understand the technical solution of the present invention, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0065] It should be understood that the specific embodiments and drawings described herein are only used to explain the present invention rather than to limit the present invention.

[0066] It can be understood that, in the absence of conflict, the various embodiments of the present invention and the various features in the embodiments can be combined with each other.

[0067] It can be understood that, for the convenience of description, the drawings of the present invention only show the parts related to the present invention, while the parts irrelevant to the present invention are not shown in the drawings.

[0068] It can be understood that each unit and module involved in the embodiments of the present invention may correspond to only one physical structure, or may be composed of multiple physical structures, or multiple units and modules may be integrated into one physical structure.

[0069] It can be understood that, without conflict, the functions and steps marked in the flowcharts and block diagrams of the present invention may occur in an order different from that marked in the drawings.

[0070] It is understood that the flowcharts and block diagrams of the present invention illustrate the possible architectures, functions, and operations of the systems, devices, equipment, and methods according to the various embodiments of the present invention. Each box in the flowchart or block diagram may represent a unit, module, program segment, or code, which contains executable instructions for implementing the specified functions. Moreover, each box or combination of boxes in the block diagram and flowchart may be implemented by a hardware-based system that implements the specified functions, or may be implemented by a combination of hardware and computer instructions.

[0071] It can be understood that the units and modules involved in the embodiments of the present invention can be implemented by software or hardware. For example, the units and modules can be located in a processor.

[0072] Embodiment 1:

[0073] like Figure 1 and Figure 3 As shown, this embodiment provides a fault location method for an information communication system. The method is widely applicable to multiple scenarios such as telecommunications operators, data centers, and Internet service providers. This method can quickly and accurately identify and locate faults, ensure the stability and reliability of the communication system, improve service quality, and reduce the risk of business interruption, thereby ensuring the normal operation of users and businesses. The method includes the following steps:

[0074] Step S0: construct a diagnostic algorithm library;

[0075] The step S0 specifically includes the following steps:

[0076] Obtain historical fault data of information and communication systems;

[0077] Use clustering algorithm to classify the historical fault data of information communication system and obtain different fault classification data;

[0078] According to the fault classification data, the original fault diagnosis model is trained to obtain a fault diagnosis model, wherein the fault diagnosis model includes a fault cause and a diagnosis strategy;

[0079] Among them, different information communication system faults correspond to different original fault diagnosis models; the original fault diagnosis model is constructed based on the selected machine learning model or deep learning model.

[0080] The main task of step S0 is to build an efficient diagnostic algorithm library for fault location and analysis of information communication systems.

[0081] The construction process of the diagnostic algorithm library is as follows:

[0082] First, it is necessary to obtain historical fault data of the information and communication system. The historical fault data of the information and communication system can be obtained by consulting system logs, querying databases, using fault management systems, using performance monitoring tools, analyzing internal documents of the organization, and collecting user feedback, so as to fully understand the fault records and trends of the system. These data are the basis for fault diagnosis, and usually include information such as the time, type, scope of impact, processing time, and solution of the fault. Through the systematic collection and organization of these data, comprehensive data support can be provided for subsequent model training and fault analysis, and the foundation for subsequent mining of fault modes can also be laid.

[0083] Next, using clustering algorithms to classify the collected historical fault data is a key step. Clustering algorithms (such as K-means, hierarchical clustering, etc.) can classify similar fault types into the same group based on the characteristics of the fault data, thereby forming clear fault classification data. This step not only helps to identify and summarize the patterns of various types of faults, but also provides accurate training data for subsequent fault diagnosis models, enabling the model to adapt to different fault situations more effectively.

[0084] Finally, based on the classified fault data, the original fault diagnosis model is trained to generate a fault diagnosis model that can identify the cause of the fault and the corresponding diagnostic strategy. The selected model can be a machine learning model (such as decision tree, random forest) or a deep learning model (such as neural network), and the specific choice depends on the application scenario and data characteristics. At the same time, different types of information and communication system faults may correspond to different original fault diagnosis models, so the flexibility and pertinence of the model are crucial. The construction of this system not only improves the accuracy of fault diagnosis, but also helps to improve the response speed and processing efficiency of the information and communication system when encountering faults.

[0085] Step S1: Acquire various operation information data of the information communication system.

[0086] The step S1 specifically includes the following steps:

[0087] Step S11: monitor network traffic in real time and collect network traffic data through a network probe; and extract stored log information from a log server to obtain log data of an information communication system; and obtain device status information through a device interface;

[0088] The network traffic data includes network data packets, traffic patterns, and bandwidth usage; the device status information includes the device's CPU usage, memory status, port status, and connection status.

[0089] Network probes, log servers, and device interfaces play an important role in information communication systems. Network probes are responsible for real-time monitoring of network traffic and collecting relevant data, including network packets, traffic patterns, and bandwidth usage. Through comprehensive monitoring of network traffic, network probes can promptly identify potential network problems or abnormalities, thereby ensuring the normal operation of the network. At the same time, log servers are used to store and manage system log information. These logs record various events during the operation of the system, providing an important basis for troubleshooting and performance analysis. By extracting the log information stored in the log server, the system can obtain comprehensive log data, and then analyze the operation status of the information communication system, identify historical faults and their trends. In addition, the device interface is used to communicate effectively with various network devices and collect device status information. This device status information usually includes the device's CPU usage, memory status, port status, and connection status. This information can not only help operation and maintenance personnel monitor the health of the device in real time, but also provide data support for the overall performance optimization of the system. By integrating the data collected by network probes, log servers, and device interfaces, the system can achieve comprehensive monitoring and analysis, thereby improving the reliability and stability of the information communication system.

[0090] Step S12: Integrate the network traffic data, the log data and the device status information to obtain various operation information data of the information communication system.

[0091] As a specific implementation, after step S1 and before step S2, the method further includes step K;

[0092] Step K: preprocessing the operation information of the information communication system;

[0093] The step K specifically comprises the following steps:

[0094] Step K1: Cleaning the operation information data of the information communication system to obtain cleaned operation information data;

[0095] Wherein, the data cleaning includes identifying and deleting random noise in the operation information data, and removing detection abnormal values ​​in the operation information data;

[0096] Step K2: extracting features from the cleaned operation information data to obtain extracted feature information;

[0097] Step K3: storing the extracted characteristic information to complete the preprocessing of the operation information of the information communication system.

[0098] The purpose of step K is to preprocess the operation information of the information and communication system to improve the accuracy and efficiency of subsequent data analysis and fault diagnosis. Specifically, first in step K1, the operation information data is cleaned. This process includes identifying and deleting random noise and removing detected abnormal values ​​to ensure the accuracy and reliability of the data, thereby eliminating interference factors that may have a negative impact on the analysis results. The cleaned data provides a solid foundation for subsequent steps. In step K2, feature extraction is performed on the cleaned operation information data to extract key feature information. These features may include system performance indicators, traffic patterns, equipment status, etc., to help operation and maintenance personnel better understand the operation status of the system, reduce data dimensions and focus on important indicators. Finally, in step K3, the extracted feature information is effectively stored, which not only promotes the structured management of data and facilitates subsequent rapid retrieval and utilization, but also provides valuable support for data mining and trend analysis. Through this series of preprocessing steps, the quality and effectiveness of the operation information of the information and communication system have been significantly improved, laying a solid foundation for system health monitoring and fault location.

[0099] Step S2: using the fault diagnosis algorithm in the diagnosis algorithm library, perform fault analysis on various operation information data of the information communication system to obtain the fault result of the information communication system; the fault diagnosis algorithm is obtained by continuous learning and optimization of the self-learning module.

[0100] In information and communication systems, it is crucial to use the fault diagnosis algorithms in the diagnostic algorithm library to perform fault analysis on various operating information data. First, the system will input the collected operating information data into the fault diagnosis algorithm. These data may involve network traffic, device status, log records and other aspects. After continuous learning and optimization by the self-learning module, the fault diagnosis algorithm can automatically analyze historical data and identify fault modes, thereby achieving accurate evaluation and fault diagnosis of the current operating status. This self-learning process not only improves the adaptability and accuracy of the algorithm to complex faults, but also enables the algorithm to continuously adjust and optimize its diagnostic strategy based on emerging data and experience, and enhance the system's ability to predict future faults. In this way, the system can eventually generate detailed fault results, clarify the type, cause and scope of the fault, provide strong support for the decision-making of operation and maintenance personnel, and ensure that the information and communication system always maintains efficient and stable operation.

[0101] Step S3: Match the fault location according to the fault result to complete the fault location for the information communication system.

[0102] After obtaining the fault results, the next step is to match the fault location based on these results to achieve accurate fault location of the information and communication system. Specifically, the system will compare the fault type, severity and related indicators provided by the fault diagnosis algorithm with the predefined fault location mapping database. This database contains detailed information on various devices and components in the information and communication system, including their functions, interconnections and historical fault records. Through this comparison, the system can quickly determine the specific location where the fault may occur, such as a certain network device, switch or specific communication link. In addition, based on the fault results, the system can also analyze the scope of the fault and identify which devices or users are affected, so as to more accurately lock the source of the fault. In this process, intelligent monitoring and visualization tools can also be used to help operation and maintenance personnel clearly understand the distribution and impact of the fault, so as to facilitate targeted maintenance and repair. In short, by matching the fault results with the fault location, the information and communication system can locate the fault in the shortest time and take quick measures to ensure the stable operation of the system and the continuity of services.

[0103] Step S4: inputting the fault result and the fault location into the fault diagnosis algorithm in the diagnosis algorithm library to form a new fault diagnosis algorithm.

[0104] Inputting the acquired fault results and corresponding fault locations into the fault diagnosis algorithm to form a new fault diagnosis algorithm is a key step in improving fault management and analysis capabilities. Specifically, this process first generates targeted input by combining detailed information about the fault results (such as fault type, impact, and occurrence time) with the specific location data of the fault location. This input not only contains real-time fault information, but also covers fault history data and prior knowledge of the corresponding equipment. Next, the fault diagnosis algorithm uses this information for deeper analysis to generate new diagnostic rules and strategies. This feedback-based data-driven approach enables the algorithm to quickly adapt to environmental changes and provide more accurate diagnosis when faced with similar faults. For example, the system can identify the relationship between fault mode and location to better predict potential risks and optimize the processing process. Through this continuous self-update mechanism, the newly formed fault diagnosis algorithm will greatly improve the accuracy and response speed of fault detection, and help the operation and maintenance team to formulate more effective maintenance strategies, ultimately improving the reliability and stability of the information and communication system.

[0105] Step S5: Issue a fault alarm according to the fault result, display the fault handling process, and record the entire process of fault handling.

[0106] Fault alarm based on fault results is one of the important response mechanisms of information and communication systems. After the fault is accurately identified and located, the system will automatically generate corresponding alarm information and push it to the operation and maintenance team in a timely manner. These alarms usually include the type of fault, severity, affected equipment or services, and preliminary fault analysis results, so that the operation and maintenance personnel can quickly understand the overall situation of the problem and the priority direction of handling. In addition, the system will also display the entire process of fault handling in real time, including the time when the fault occurred, the time when the alarm was generated, each link of the handling, and the specific measures taken by the operation and maintenance personnel, such as restarting the device, repairing the network connection, or performing other necessary troubleshooting operations. This process not only provides a clear fault handling path for the operation and maintenance personnel, but also ensures the consistency and efficiency of team collaboration. At the same time, all fault handling steps and operations will be recorded in detail, including the details of each processing, the adjusted parameters, the results of the verification, etc. These records can not only be used for subsequent fault tracing and analysis, helping the team to summarize experience and optimize the processing process, but also provide valuable data support and reference for similar faults in the future, thereby continuously improving the stability and fault response capabilities of the system. Through this comprehensive fault alarm and processing record mechanism, the information communication system can achieve more efficient fault management, ensuring service continuity and user satisfaction. This embodiment can efficiently and accurately locate the fault of the information communication system by the electronic device, thereby improving the efficiency and quality of fault diagnosis and ensuring the reliability and stability of the system.

[0107] like Figure 2 As shown, the working principle of this embodiment is as follows: first, the system operation status is monitored in real time, and various data information is collected, including but not limited to network traffic, device status, log files, etc. These data are pre-processed by the data processing module, including data cleaning, feature extraction and data storage, to provide high-quality data support for subsequent fault analysis. Then, the algorithm in the preset diagnosis algorithm library is used to perform fault location analysis according to the feature information provided by the data processing module. The diagnosis engine selects a suitable algorithm for fault analysis according to the feature information, generates a specific fault handling solution based on the diagnosis result, and guides relevant equipment or personnel to handle the fault. Then, data mining is performed through the self-learning module to extract valuable information from the historical fault data. The algorithm optimization unit optimizes the diagnosis algorithm according to the extracted information, and the knowledge base update unit updates the fault handling knowledge base. The introduction of this module enables the system to continuously adapt to changes in the network environment and continuously improve the performance of the fault diagnosis algorithm. The user interface module provides an intuitive interactive interface, allowing users to easily view the system status, fault information and handling solutions. The alarm module sends alarm information to relevant personnel in a timely manner when a fault is detected to ensure that a timely response can be made when a fault occurs. The fault recording module records all fault events and processing processes in the system to provide detailed data support for subsequent analysis and auditing. Through the collaborative work of the above modules, not only the fault handling capability of the information communication system is improved, but also a strong guarantee for the long-term stable operation of the system is provided. Through continuous learning and optimization, the present invention can adapt to complex and changeable network environments, quickly and accurately locate faults, reduce manual intervention, and shorten fault handling time, thereby improving the stability and reliability of the entire information communication system.

[0108] Embodiment 2:

[0109] like Figure 4 As shown, this embodiment provides a fault location device for an information communication system, the device comprising:

[0110] The acquisition unit 10 is used to acquire various operation information data of the information communication system;

[0111] The analysis unit 20 is connected to the acquisition unit 10 and is used to perform fault analysis on various operation information data of the information communication system using the fault diagnosis algorithm in the diagnosis algorithm library to obtain the fault result of the information communication system;

[0112] Wherein, the fault diagnosis algorithm is obtained by continuous learning and optimization through a self-learning module;

[0113] The matching unit 30 is connected to the analyzing unit 20 and is used to match the fault location according to the fault result to complete the fault location for the information communication system.

[0114] As a specific implementation, the acquisition unit 10 includes:

[0115] A first acquisition module is used to monitor network traffic in real time and collect network traffic data through a network probe;

[0116] A second acquisition module is used to extract the stored log information from the log server to obtain the log data of the information communication system;

[0117] A third acquisition module is used to obtain device status information through a device interface;

[0118] The network traffic data includes network data packets, traffic patterns, and bandwidth usage; the device status information includes the device's CPU usage, memory status, port status, and connection status;

[0119] The integration module is connected to the first acquisition module, the second acquisition module and the third acquisition module, and is used to integrate the network flow data, the log data and the device status information to obtain various operation information data of the information communication system.

[0120] As a specific embodiment, the device further includes a construction unit;

[0121] The building block comprises:

[0122] An acquisition subunit, used for acquiring historical fault data of the information communication system;

[0123] A classification subunit, connected to the acquisition subunit, for classifying the historical fault data of the information communication system using a clustering algorithm to obtain different fault classification data;

[0124] A training subunit, connected to the classification subunit, for training the original fault diagnosis model according to the fault classification data to obtain a fault diagnosis model, wherein the fault diagnosis model includes a fault cause and a diagnosis strategy;

[0125] Among them, different information communication system faults correspond to different original fault diagnosis models; the original fault diagnosis model is constructed based on the selected machine learning model or deep learning model.

[0126] Embodiment 3:

[0127] This embodiment provides a fault location system for an information communication system, the system comprising:

[0128] A fault location module, used to execute the fault location method for an information communication system as described in Example 1, and obtain fault location data whose fault result matches the fault location;

[0129] A data storage module, which is in communication connection with the fault location module and is used to store fault location data of the information communication system;

[0130] A user interaction module is connected to the data storage module for displaying the fault location data in the data storage module.

[0131] It is to be understood that the above embodiments are merely exemplary embodiments used to illustrate the principles of the present invention, but the present invention is not limited thereto. For those of ordinary skill in the art, various modifications and improvements can be made without departing from the spirit and essence of the present invention, and these modifications and improvements are also considered to be within the scope of protection of the present invention.

Claims

1. A fault location method for an information communication system, characterized in that: The method comprises the following steps: Step S1: Acquire operation information data of the information communication system; Step S2: using the fault diagnosis algorithm in the diagnosis algorithm library to perform fault analysis on the operation information data of the information communication system to obtain the fault result of the information communication system; Wherein, the fault diagnosis algorithm is obtained by continuous learning and optimization through a self-learning module; Step S3: Match the fault location according to the fault result to complete the fault location for the information communication system.

2. The fault location method for an information communication system according to claim 1, characterized in that: The step S1 specifically includes the following steps: Step S11: monitor network traffic in real time and collect network traffic data through a network probe; and extract stored log information from a log server to obtain log data of an information communication system; and obtain device status information through a device interface; The network traffic data includes network data packets, traffic patterns, and bandwidth usage; the device status information includes the device's CPU usage, memory status, port status, and connection status; Step S12: Integrate the network traffic data, the log data and the device status information to obtain operation information data of the information communication system.

3. The fault location method for an information communication system according to claim 1, characterized in that: After step S1 and before step S2, the method further includes step K; Step K: preprocessing the operation information data of the information communication system; The step K specifically comprises the following steps: Step K1: Cleaning the operation information data of the information communication system to obtain cleaned operation information data; Wherein, the data cleaning includes identifying and deleting random noise in the operation information data, and removing detection abnormal values ​​in the operation information data; Step K2: extracting features from the cleaned operation information data to obtain extracted feature information; Step K3: storing the extracted characteristic information to complete the preprocessing of the operation information of the information communication system.

4. The fault location method for an information communication system according to claim 1, characterized in that: After step S3, the method further includes step S4; Step S4: inputting the fault result and the fault location into the fault diagnosis algorithm in the diagnosis algorithm library to form a new fault diagnosis algorithm.

5. The fault location method for an information communication system according to claim 1, characterized in that: After step S3, the method further includes step S5; Step S5: Issue a fault alarm according to the fault result, display the fault handling process, and record the entire process of fault handling.

6. The fault location method for an information communication system according to any one of claims 1 to 5, characterized in that: Before step S2, the method further includes: Step S0: construct a diagnostic algorithm library; The step S0 specifically includes the following steps: Obtain historical fault data of information and communication systems; Use clustering algorithm to classify the historical fault data of information communication system and obtain different fault classification data; According to the fault classification data, the original fault diagnosis model is trained to obtain a fault diagnosis model, wherein the fault diagnosis model includes a fault cause and a diagnosis strategy; Among them, different information communication system faults correspond to different original fault diagnosis models; the original fault diagnosis model is constructed based on the selected machine learning model or deep learning model.

7. A fault location device for an information communication system, characterized in that: The device comprises: An acquisition unit, used to acquire operation information data of the information communication system; An analysis unit connected to the acquisition unit, used to perform fault analysis on the operation information data of the information communication system using a fault diagnosis algorithm in a diagnosis algorithm library to obtain a fault result of the information communication system; Wherein, the fault diagnosis algorithm is obtained by continuous learning and optimization through a self-learning module; A matching unit is connected to the analyzing unit and is used to match the fault location according to the fault result to complete the fault location for the information communication system.

8. The fault location device for an information communication system according to claim 7, characterized in that: The acquisition unit comprises: A first acquisition module is used to monitor network traffic in real time and collect network traffic data through a network probe; A second acquisition module is used to extract the stored log information from the log server to obtain the log data of the information communication system; A third acquisition module is used to obtain device status information through a device interface; The network traffic data includes network data packets, traffic patterns, and bandwidth usage; the device status information includes the device's CPU usage, memory status, port status, and connection status; An integration module is connected to the first acquisition module, the second acquisition module and the third acquisition module, and is used to integrate the network flow data, the log data and the device status information to obtain operation information data of the information communication system.

9. The fault location device for an information communication system according to claim 7 or 8, characterized in that: The device also includes a construction unit; The building block comprises: An acquisition subunit, used for acquiring historical fault data of the information communication system; A classification subunit, connected to the acquisition subunit, for classifying the historical fault data of the information communication system using a clustering algorithm to obtain different fault classification data; A training subunit, connected to the classification subunit, for training the original fault diagnosis model according to the fault classification data to obtain a fault diagnosis model, wherein the fault diagnosis model includes a fault cause and a diagnosis strategy; Among them, different information communication system faults correspond to different original fault diagnosis models; the original fault diagnosis model is constructed based on the selected machine learning model or deep learning model.

10. A fault location system for an information communication system, characterized in that: The system comprises: A fault location module, used to execute the fault location method for an information communication system according to any one of claims 1 to 6, and obtain fault location data whose fault result matches the fault location; A data storage module, which is in communication connection with the fault location module and is used to store fault location data of the information communication system; A user interaction module is connected to the data storage module for displaying the fault location data in the data storage module.

Images