CN112836972A - IT equipment fault defect processing system and fault defect processing method - Google Patents
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Abstract
The invention discloses an IT equipment fault defect processing system and a fault defect processing method, wherein a data support platform is accessed into IT equipment and senses and acquires operation data of the IT equipment, the operation data of the IT equipment acquired by the data support platform is extracted through an intelligent engine module, a fault knowledge base system with a knowledge extraction function is constructed aiming at the extracted operation data, an auxiliary decision service is provided for the quick fault first-aid repair service of the IT equipment, an intelligent assistant engine is deployed at an application front end, fault knowledge is extracted and identified, the fault knowledge base system is associated to form one-to-one corresponding fault knowledge maps, and then the fault knowledge maps of the IT equipment are managed and visually displayed. The invention can monitor the operation data of the IT equipment in time, and the IT equipment fault analysis based on the knowledge map enables the maintenance personnel of the IT equipment to conveniently and rapidly carry out fault inquiry and fault treatment, thereby effectively improving the fault diagnosis level of the IT equipment.
Description
Technical Field
The application belongs to the technical field of equipment fault processing, and particularly relates to an IT equipment fault defect processing system and a fault defect processing method.
Background
The knowledge construction of the power industry depends on a large amount of manual carding, summarizing and refining work, the development requirements are difficult to adapt today when the industrial data is increased explosively, the data quality of each text data is good and uneven due to the diversity of power text data sources and service scenes, and the data quality is directly related to the quality of a finally formed knowledge graph facing to the power grid master equipment. In recent years, due to the wide attention of all the social circles to the knowledge graph, the knowledge graph research has been greatly developed. At present, research progress of knowledge extraction, knowledge map construction, entity alignment, knowledge representation learning and knowledge fusion are researched at home and abroad to a certain extent. However, related knowledge research is mostly applied to solving the problem of universality or simple problems, and still lacks of a system, deep combing and summarizing of knowledge graph knowledge reasoning research for main equipment of a power grid and lacks of universality. Therefore, in order to ensure the quality of the knowledge graph of the main equipment of the power grid, efficient and automatic mining of a knowledge graph reasoning rule needs to be realized, the cost consumed by long-term complicated artificial knowledge construction is reduced, an efficient quality evaluation system needs to be established aiming at the text resource data of the existing power grid industry, a quality evaluation model adaptive to the service requirement is provided for a user, abstract evaluation is converted into a quantifiable index, the misjudgment rate is reduced, and a more accurate and objective resource evaluation process is realized.
Disclosure of Invention
The invention aims to provide an IT equipment fault defect processing system and a fault defect processing method, which can process the operation data of IT equipment in time and carry out IT equipment fault analysis based on a knowledge graph, so that IT equipment maintenance personnel can conveniently and rapidly inquire and process fault defects, the fault diagnosis level of the IT equipment is effectively improved, and the production, operation and safe driving and protection of the IT equipment are realized. In order to achieve the above object, the present invention adopts the following technical effects:
according to an aspect of the present invention, there is provided an IT device fault defect handling system, the fault analysis system including: the intelligent fault management system comprises a data supporting platform, an intelligent engine module and an intelligent assistant engine, wherein the data supporting platform is used for accessing IT equipment and perceiving and acquiring operation data of the IT equipment, the intelligent engine module is used for extracting the operation data of the IT equipment acquired by the data supporting platform, a fault defect knowledge base system with a knowledge extraction function is constructed aiming at the extracted operation data, an assistant decision service is provided for the quick fault repair service of the IT equipment, the intelligent assistant engine is deployed at the application front end and used for extracting fault knowledge and identifying abnormal modes, the fault knowledge base system is associated to form a fault knowledge map in one-to-one correspondence, and then the knowledge map of the faults of the IT equipment is managed and visually displayed.
Preferably, the establishing a fault defect knowledge base system with a knowledge extraction function includes: extracting the structured information of the operating data based on semantic information to obtain a knowledge graph of valuable entities, relations and attributes, forming an IT equipment fault corpus for extracting the knowledge graph, automatically identifying the unstructured knowledge graph by adopting a natural language technology on the basis of the IT equipment fault corpus, and associating the related entities of IT equipment fault knowledge and the relations thereof to generate the knowledge graph with multi-semantic knowledge fusion.
Further preferably, the data support platform includes one or more of an IOS system, an ITSM system, a PDP system, and a wiki system.
Preferably, the intelligent assistant engine comprises an extraction module, an identification module, a decision module, an evaluation module and a query display module; the extraction module is used for acquiring a knowledge graph with multiple semantic inputs and extracting question information of the knowledge graph with multiple semantic inputs; the recognition module is used for analyzing the semantic format of the question information to acquire a knowledge graph of the user; the decision module is used for acquiring the knowledge graph of the current user to perform online fault judgment and maintenance decision, and providing intelligent auxiliary decision for maintainers; the inquiry display module is used for inquiring information according to data input by a user, inquiring an optimal treatment and maintenance case from a knowledge graph of IT equipment faults through a machine reasoning algorithm, and visually displaying the inquired optimal treatment and maintenance case to the user and implementing the optimal treatment and maintenance case.
Preferably, the best treatment and maintenance case is inquired from the knowledge graph of the IT equipment fault through the machine reasoning algorithm, the data provided by user input is analyzed through the NLP algorithm to inquire, the user natural expression is converted into an inquiry subgraph, graph search is carried out in the knowledge graph of the IT equipment, the optimal graph node is matched, and corresponding information is returned, so that the fault processing scheme is positioned.
According to another aspect of the invention, the invention provides an IT equipment fault defect processing method, which comprises the steps of extracting operation data of IT equipment acquired by a data support platform through an intelligent engine module, constructing a fault knowledge base system with a knowledge extraction function aiming at the extracted operation data, providing an auxiliary decision service for an IT equipment fault rapid first-aid repair service, deploying an intelligent assistant engine at an application front end, extracting and identifying fault knowledge, associating the fault knowledge base system based on the fault knowledge base system to form one-to-one corresponding fault knowledge maps, and managing and visually displaying the IT equipment fault knowledge maps.
Preferably, the method for establishing a fault defect knowledge base system with knowledge extraction function comprises the following steps: extracting the structured information of the operating data based on semantic information to obtain a knowledge graph of valuable entities, relations and attributes so as to form an IT equipment fault corpus for extracting the knowledge graph, automatically identifying an unstructured knowledge graph by adopting a natural language technology on the basis of the IT equipment fault corpus, associating related entities of IT equipment fault knowledge and the relations among the related entities, and then generating the knowledge graph with multi-semantic knowledge fusion.
Preferably, the intelligent assistant engine acquires a knowledge graph with multiple semantic inputs and extracts question information of the knowledge graph with multiple semantic inputs; and then, analyzing semantic formats of the question information to acquire a knowledge graph of the user, performing online fault judgment and maintenance decision on the knowledge graph of the current user to provide intelligent auxiliary decision for maintainers, inquiring the best disposal maintenance case from the knowledge graph of the IT equipment fault through a machine reasoning algorithm according to the data inquiry information input by the user, and visually displaying the inquired best disposal maintenance case to the user and implementing the best disposal maintenance case.
Further preferably, the parsing result in the semantic format includes one or more of entity information, relationship information, and attribute information.
In summary, due to the adoption of the technical scheme, the invention has the following technical effects:
(1) the fault platform can monitor the operation data of the IT equipment in time, and process and analyze the fault defects of the IT equipment based on the knowledge graph, so that the maintenance personnel of the IT equipment can conveniently and rapidly perform fault inquiry and fault processing, the fault diagnosis level of the IT equipment is effectively improved, and the production, operation, driving protection and navigation of the IT equipment are realized.
(2) The IT equipment fault defect processing system can quickly collect the IT equipment fault information and quickly dispose the problems, can timely provide maintenance aid decision and quickly dispose the fault abnormity for judgment and analysis, and can ensure the quality of the knowledge base when visually displayed to a user and implemented and executed.
Drawings
FIG. 1 is a schematic diagram of an IT equipment fault defect handling system of the present invention;
FIG. 2 is a schematic diagram of the intelligent assistant engine of the present invention
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail below with reference to the accompanying drawings by way of examples of preferred embodiments. It should be noted, however, that the numerous details set forth in the description are merely for the purpose of providing the reader with a thorough understanding of one or more aspects of the present invention, which may be practiced without these specific details.
With reference to fig. 1, the present invention provides an IT device fault defect handling system, wherein the fault analysis system comprises: the intelligent engine module is arranged at the front end of the application and used for extracting fault knowledge and identifying abnormal modes, associating the fault knowledge and knowledge base system to form one-to-one corresponding fault knowledge maps, managing and visually displaying the fault knowledge maps of the IT equipment, and acquiring the operation data of the IT fault equipment when the IT equipment is detected to have faults, wherein the operation data comprises equipment manufacturers, equipment names, and the like, The model, the rated capacity of the equipment, the voltage level, the commissioning place, the commissioning time, the line name, the line length, the type of the fault element, the reason, the processing measure and other key information. In the invention, establishing a fault defect knowledge base system with a knowledge extraction function comprises the following steps: extracting the structured information of the operating data based on semantic information to obtain a knowledge graph with valuable entities, relations and attributes, forming an IT equipment fault corpus for extracting the knowledge graph, automatically identifying an unstructured knowledge graph by adopting a natural language technology on the basis of the IT equipment fault corpus, associating related entities of IT equipment fault knowledge and the relations among the related entities to generate a knowledge graph with multi-semantic knowledge fusion; the data support platform comprises one or more of an IOS system, an ITSM system, a PDP system and a wiki system; the data support platform is accessed to a communication interface of the IT equipment and monitors the health condition of the IT equipment in real time, the communication interface acquires equipment information once every 5 minutes, then the equipment information is processed by tools such as a D2R (DRF format converter) and a wrapper (format analysis tool), all data are finally converted into standard data for use by a map through processing, the standard data are sent into a Neo4j map database to manage and visualize knowledge, related entities of 'state-phenomenon-equipment-symptom-reason-processing suggestion' IT equipment fault knowledge and inference maps and the relationship among the related entities are associated in a knowledge map form, the processed related information is stored in a fault defect knowledge base system, and finally, the visualization display is carried out, so that the automatic visualization efficiency of fault data is improved, or redundant graphs existing in automatically generated visualization graphs are reduced, the user understanding and analysis are facilitated. The IOS system is used for acquiring real-time data monitoring information of IT equipment fault operation state, for example: acquiring related information such as the real-time temperature of the CUP of the server equipment, the real-time memory of a disk and the like; an ITSM system interface accessed by the data support platform reads an IT equipment fault processing report, wherein the IT equipment fault processing report mainly comprises equipment online monitoring data, historical state monitoring data, alarm information, an equipment operation and maintenance work order, a processing equipment model, a processing event reason, a processing event description, an event processing method, an event processing result and other related information which are acquired by monitoring equipment and a sensor in ITSM; the PDP system is used to obtain IT device ledger data, for example: the KKS code of the equipment account, the position of the equipment, the model of the equipment and other related information; wiki systems are used to obtain information data about IT devices, such as: server device specification, device production date, device rating parameters, device threshold and the like.
In the invention, with reference to fig. 1 and fig. 2, the intelligent assistant engine includes an extraction module, a recognition module, a decision module, an evaluation module and a query presentation module; the extraction module is used for acquiring a knowledge graph with multiple semantic inputs and extracting question information of the knowledge graph with multiple semantic inputs; the recognition module is used for analyzing the semantic format of the question information to acquire a knowledge graph of the user, wherein the analysis result of the semantic format comprises entity information, relationship information or attribute information; the decision module is used for acquiring a knowledge graph of a current user to perform online fault judgment and maintenance decision, providing intelligent auxiliary decision for a maintainer, and aiming at an IT equipment operation and maintenance person, the decision module can see a list of faults and abnormity of the whole IT equipment and a certain defect and fault information summary panorama, and the process of 'state investigation-phenomenon inquiry-equipment analysis-data analysis-gradual elimination' is carried out, so that the range of causes is gradually reduced, the diagnosis accuracy is improved, the intelligent auxiliary decision is provided for the maintainer, and processing advice and case recommendation based on different fault levels are realized; the query display module is used for querying information according to data input by a user, querying an optimal handling and maintenance case from an IT equipment fault knowledge graph through a machine inference algorithm, visually displaying the queried optimal handling and maintenance case to the user and implementing the optimal handling and maintenance case, and in the invention, the optimal handling and maintenance case queried from the IT equipment fault knowledge graph through the machine inference algorithm is queried based on data input by the user and converted into a query subgraph, graph search (question and sentence intention pattern recognition, entity link and inference) is carried out in the IT equipment knowledge graph, and corresponding information is returned by matching to an optimal graph node, so that a fault processing scheme is positioned; the intelligent assistant engine is deployed at the front end of the application and is used for supporting visual operation and natural language input, wherein the visual operation and the natural language input comprise a text mode and a voice mode; for the query input by the user, a query subgraph can be accurately generated through entity identification, and the graph application is carried out, for example, a corresponding judgment conclusion, a treatment scheme, a case and the like are fed back according to the user input, the query information input by the user is intelligently queried and matched to an optimal rule operation action or case according to a machine reasoning algorithm, and then the optimal rule operation action or case is pushed to a related role for confirmation and then executed, so that IT equipment maintenance personnel can conveniently and quickly query and process faults, the fault diagnosis level of the IT equipment is effectively improved, and the production, operation and driving protection of the IT equipment are realized.
According to another aspect of the invention, in combination with fig. 1 and 2, the invention provides an IT equipment fault defect processing method: the method comprises the following steps of accessing a data support platform into IT equipment, sensing and acquiring operation data of the IT equipment, extracting the operation data of the IT equipment acquired by the data support platform through an intelligent engine module, constructing a fault knowledge base system with a knowledge extraction function aiming at the extracted operation data, providing an auxiliary decision service for the rapid repair service of the IT equipment faults, deploying an intelligent assistant engine at the front end of an application, extracting and identifying fault knowledge, associating the fault knowledge base system based on the fault knowledge base system to form one-to-one corresponding fault defect knowledge maps, and managing and visually displaying the fault knowledge maps of the IT equipment. In some of the inventions, establishing a fault defect knowledge base system with knowledge extraction function includes the following steps: extracting semantic-based information from structured information of operating data to obtain a knowledge graph with valuable entities, relations and attributes so as to form an IT equipment fault defect corpus for extracting the knowledge graph, automatically identifying an unstructured knowledge graph by adopting a natural language technology on the basis of the IT equipment fault defect corpus, associating related entities of IT equipment fault defect knowledge and the relations among the related entities, and then generating a knowledge graph with multi-semantic knowledge fusion; then, semantic format analysis is carried out on the question information to obtain a knowledge graph of the user, the analysis result of the semantic format comprises one or more of entity information, relationship information and person attribute information, and the relation between the entities is extracted from the knowledge graph text with multiple senses, namely the question is asked according to the relation result between the entities obtained by extraction; firstly, entity items are obtained from a knowledge graph text through entity extraction, then entity disambiguation and coreference resolution are carried out, whether the same-name entities in an IT equipment fault corpus represent different meanings or not and whether other named entities in the IT equipment fault corpus represent the same meanings or not are judged, and after the correct entity objects in the IT equipment fault corpus are confirmed, the entity names are linked to the corresponding entities in the IT equipment fault corpus; on the basis of an IT equipment fault corpus, automatically identifying unstructured by using a natural language technology, and analyzing, extracting and constructing relations among entities by adopting a machine learning method of entity identification and entity relation extraction; through information extraction, knowledge elements such as entities, relations, attributes and the like can be extracted from an original IT equipment fault defect corpus, and then knowledge fusion is performed, so that ambiguity between entity nominal items and entity objects can be eliminated, and a series of basic fact expressions are obtained. Therefore, the equipment fault quality is evaluated, then the knowledge graph of the current user is subjected to online fault judgment and maintenance decision, intelligent auxiliary decision is provided for maintenance personnel, the best handling and maintenance case is inquired from the knowledge graph of the IT equipment fault through a machine reasoning algorithm according to data inquiry information provided by user input, the inquired best handling and maintenance case is visually displayed to the user and is implemented, and the machine reasoning algorithm starts from the entity relation data in the IT equipment fault corpus to carry out computer reasoning and establish new association among entities, so that the new knowledge graph can be found from the original knowledge, the credibility of the knowledge graph can be quantified, and the knowledge with lower confidence coefficient is abandoned, when the knowledge base is visually displayed to a user and implemented, the quality of the knowledge base can be guaranteed.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that those skilled in the art can make various improvements and modifications without departing from the principle of the present invention, and these improvements and modifications should also be construed as the protection scope of the present invention.
Claims (9)
1. An IT equipment fault defect handling system, characterized by: the fault handling system includes: the intelligent fault diagnosis system comprises a data supporting platform, an intelligent engine module and an intelligent assistant engine, wherein the data supporting platform is used for accessing IT equipment and perceiving and acquiring operation data of the IT equipment, the intelligent engine module is used for extracting the operation data of the IT equipment acquired by the data supporting platform, a fault defect knowledge base system with a knowledge extraction function is constructed aiming at the extracted operation data, an assistant decision service is provided for the quick fault repair service of the IT equipment, the intelligent assistant engine is deployed at the application front end and used for extracting fault knowledge and identifying abnormal modes, the fault knowledge base system is associated to form a one-to-one corresponding fault knowledge map, and then the knowledge map of the fault defects of the IT equipment is managed and visually displayed.
2. The IT equipment fault defect handling system of claim 1, wherein: establishing a fault defect knowledge base system with a knowledge extraction function comprises the following steps: extracting the structured information of the operating data based on semantic information to obtain a knowledge graph of valuable entities, relations and attributes, forming an IT equipment fault corpus for extracting the knowledge graph, automatically identifying the unstructured knowledge graph by adopting a natural language technology on the basis of the IT equipment fault corpus, and associating the related entities of IT equipment fault knowledge and the relations thereof to generate the knowledge graph with multi-semantic knowledge fusion.
3. The IT equipment fault defect handling system of claim 1, wherein: the data support platform includes one or more of an IOS system, an ITSM system, a PDP system, and a wiki system.
4. The IT equipment fault defect handling system of claim 1, wherein: the intelligent assistant engine comprises an extraction module, an identification module, a decision module, an evaluation module and an inquiry display module; the extraction module is used for acquiring a knowledge graph with multiple semantic inputs and extracting question information of the knowledge graph with multiple semantic inputs; the recognition module is used for analyzing the semantic format of the question information to acquire a knowledge graph of the user; the decision module is used for acquiring the knowledge graph of the current user to perform online fault judgment and maintenance decision, and providing intelligent auxiliary decision for maintainers; the inquiry display module is used for inquiring information according to data input by a user, inquiring an optimal treatment and maintenance case from a knowledge graph of IT equipment faults through a machine reasoning algorithm, and visually displaying the inquired optimal treatment and maintenance case to the user and implementing the optimal treatment and maintenance case.
5. The IT equipment fault defect handling system of claim 1, wherein: the optimal treatment and maintenance case is inquired from the knowledge graph of the IT equipment fault through the machine reasoning algorithm and inquired based on the data provided by analyzing user input through the NLP algorithm, the user natural expression is converted into an inquiry subgraph, graph search is carried out in the knowledge graph of the IT equipment, the optimal graph node is matched, and corresponding information is returned, so that the fault processing scheme is positioned.
6. An IT equipment fault defect processing method is characterized in that: the method comprises the following steps of accessing a data support platform into IT equipment, sensing and acquiring operation data of the IT equipment, extracting the operation data of the IT equipment acquired by the data support platform through an intelligent engine module, constructing a fault defect knowledge base system with a knowledge extraction function aiming at the extracted operation data, providing an auxiliary decision service for the IT equipment fault rapid repair service, deploying an intelligent assistant engine at the front end of an application, extracting and identifying fault knowledge, associating the fault knowledge base system to form one-to-one corresponding fault defect knowledge maps, and managing and visually displaying the IT equipment fault defect knowledge maps.
7. The fault defect handling method of claim 6, wherein: the method for establishing the fault defect knowledge base system with the knowledge extraction function comprises the following steps: extracting the structured information of the operating data based on semantic information to obtain a knowledge graph of valuable entities, relations and attributes so as to form an IT equipment fault corpus for extracting the knowledge graph, automatically identifying an unstructured knowledge graph by adopting a natural language technology on the basis of the IT equipment fault corpus, associating related entities of IT equipment fault knowledge and the relations among the related entities, and then generating the knowledge graph with multi-semantic knowledge fusion.
8. The fault defect handling method according to claim 1, characterized by: the intelligent assistant engine acquires a knowledge graph input in multiple meanings and extracts question information of the knowledge graph input in multiple meanings; and then, analyzing semantic formats of the question information to acquire a knowledge graph of the user, performing online fault judgment and maintenance decision on the knowledge graph of the current user to provide intelligent auxiliary decision for maintainers, inquiring the best disposal maintenance case from the knowledge graph of the IT equipment fault through a machine reasoning algorithm according to the data inquiry information input by the user, and visually displaying the inquired best disposal maintenance case to the user and implementing the best disposal maintenance case.
9. The fault defect handling method of claim 8, wherein: the parsing result of the semantic format includes one or more of entity information, relationship information, and person attribute information.
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| CN113420162A (en) * | 2021-06-24 | 2021-09-21 | 国网天津市电力公司 | Equipment operation chain state monitoring method based on knowledge graph |
| CN113592111A (en) * | 2021-07-30 | 2021-11-02 | 上海健康医学院 | Intelligent fault processing method and system for nuclear power equipment |
| CN113704487A (en) * | 2021-07-29 | 2021-11-26 | 湖南五凌电力科技有限公司 | Knowledge graph generation method and device, computer equipment and storage medium |
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