WO2021232567A1 - Procédé d'analyse de connaissances de fonctionnement et de maintenance intelligent basé sur la technologie à ia - Google Patents

Procédé d'analyse de connaissances de fonctionnement et de maintenance intelligent basé sur la technologie à ia Download PDF

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Publication number
WO2021232567A1
WO2021232567A1 PCT/CN2020/102157 CN2020102157W WO2021232567A1 WO 2021232567 A1 WO2021232567 A1 WO 2021232567A1 CN 2020102157 W CN2020102157 W CN 2020102157W WO 2021232567 A1 WO2021232567 A1 WO 2021232567A1
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Prior art keywords
maintenance
analysis
data
fault
knowledge
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PCT/CN2020/102157
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English (en)
Chinese (zh)
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陈俊桦
夏鸣
吴雪峰
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江苏南工科技集团有限公司
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Publication of WO2021232567A1 publication Critical patent/WO2021232567A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
    • G06F16/2465—Query processing support for facilitating data mining operations in structured databases
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/242—Query formulation
    • G06F16/243—Natural language query formulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/20—Administration of product repair or maintenance

Definitions

  • the invention relates to the technical field of operation and maintenance management, in particular to a method for analyzing intelligent operation and maintenance knowledge based on AI technology.
  • Operation and maintenance usually refers to the Internet operation and maintenance, which belongs to the technical department. It is essentially the operation and maintenance of each stage of the life cycle of the network, server, and service. It has reached a consensus and acceptable state in terms of cost, stability, and efficiency.
  • the current operation The maintenance method is performed by the operation and maintenance personnel after discovering the abnormal operation and resource consumption of the service, and then manually analyze and deal with it.
  • In the operation and maintenance management there are often many repeated faults, and these faults can be dealt with through a fixed solution. Manually handling these repetitive faults each time greatly wastes the time of operation and maintenance personnel and reduces the processing efficiency. For this reason, we propose a smart operation and maintenance knowledge analysis method based on AI technology to solve the above problems.
  • the purpose of the present invention is to provide a smart operation and maintenance knowledge analysis method based on AI technology to solve the problems raised in the background art.
  • an AI technology-based intelligent operation and maintenance knowledge analysis method including the following steps:
  • the AI analysis engine generates a fault handling plan, and feeds the handling plan back to the knowledge base, enriching knowledge base data;
  • the execution unit executes the operation and maintenance process according to the fault handling plan
  • step S1 the monitoring system continuously collects real-time load data of the device through collection devices such as sensors, and judges whether the device is overloaded according to the device load threshold.
  • the knowledge base includes a fault database, a solution database, a collection module, and a judgment module.
  • the fault data in the fault database corresponds to the solution data in the solution database, so
  • the collection module is used to collect the fault information and solutions processed by the operation and maintenance personnel in the past, and the judgment module determines whether the identified fault data is consistent with the implementation of the solution.
  • the AI analysis engine is connected to a manual intervention system, and the manual intervention system includes a display and an input unit for detecting the rationality of the processing plan generated by the AI analysis engine , And can actively input processing instructions through the input unit or make a selection of multiple processing schemes.
  • the AI analysis engine includes an analysis unit model for analyzing the fault data and selecting a processing plan based on the data stored in the knowledge base.
  • the method for generating the analysis unit model is as follows: constructing AI Learning framework, using historical manual operation and maintenance data as the training set of the AI learning framework to train the machine learning framework to obtain the analysis unit model, and use the parsed solution text and the answer corresponding to the input text before analysis as the AI learning.
  • the training set of the framework trains the AI learning framework and improves the analytical unit model.
  • the answer is corrected according to the statistical probability and the feedback mechanism.
  • the number of times the answer is selected is obtained, and the answer is determined.
  • the answer that has been selected the most times is the standard answer, which is stored in the analytical unit model and the knowledge base.
  • the AI analysis engine further includes a storage unit and an update training unit, the storage unit is used to store the parsed input text and answers corresponding to the fault data, and the update training unit is used to use the parsed input text The input text and answers of the analytic unit model are trained.
  • the present invention has the beneficial effects of establishing an AI analysis engine and a knowledge base, collecting the operation and maintenance data of the past operation and maintenance personnel through the analytical unit model, and performing fault data and processing solutions through the knowledge base.
  • the AI analysis engine analyzes the fault information, and then selects the corresponding processing plan from the database according to the analysis result, which greatly saves the workload of the operation and maintenance personnel, and the processing when repeated faults occur Efficiency is improved.
  • FIG. 1 is a flowchart of the present invention
  • Figure 2 is a block diagram of the knowledge base structure in the present invention.
  • an AI technology-based intelligent operation and maintenance knowledge analysis method including the following steps:
  • the AI analysis engine generates a fault handling plan, and feeds the handling plan back to the knowledge base, enriching knowledge base data;
  • the execution unit executes the operation and maintenance process according to the fault handling plan
  • step S1 the monitoring system continuously collects real-time load data of the device through collection devices such as sensors, and judges whether the device is overloaded according to the device load threshold.
  • the knowledge base includes a fault database, a solution database, a collection module, and a judgment module.
  • the fault data in the fault database corresponds to the solution data in the solution database, and the collection module is used to compare
  • the operation and maintenance personnel collects the fault information and plans that have been processed in the past, and the judgment module judges whether the identified fault data is consistent with the plan implementation.
  • the AI analysis engine is connected to the manual intervention system.
  • the manual intervention system includes a display and an input unit for detecting the rationality of the processing scheme generated by the AI analysis engine, and can pass The input unit actively inputs processing instructions or selects the best for multiple processing schemes.
  • the AI analysis engine includes an analysis unit model for analyzing the fault data and selecting a processing plan based on the data stored in the knowledge base.
  • the method for generating the analysis unit model is as follows: construct an AI learning framework to Historical manual operation and maintenance data is used as the training set of the AI learning framework to train the machine learning framework, and the analytical unit model is obtained, and the parsed plan text and the answer corresponding to the input text before the analysis are used as the training set of the AI learning framework to AI
  • the learning framework is trained to improve the analytical unit model.
  • a preferred implementation case is that after the analytical unit model parses the answer, the answer is corrected according to the statistical probability and feedback mechanism.
  • the number of times the answer is selected is obtained, and the number of times the answer is selected is determined to be the most.
  • the answer is the standard answer, which is stored in the analytical unit model and the knowledge base.
  • the AI analysis engine further includes a storage unit and an update training unit.
  • the storage unit is used to store the parsed input text and answers corresponding to the fault data
  • the update training unit is used to use the parsed input text and answer pairs. Analyze the unit model for training.
  • the invention collects the operation and maintenance data of the past operation and maintenance personnel through the analysis unit model by establishing an AI analysis engine and a knowledge base, and corresponds the fault data and the processing plan through the knowledge base, so that when repeated faults occur, the AI
  • the analysis engine analyzes the fault information, and selects the corresponding processing plan from the database according to the analysis result, which greatly saves the workload of operation and maintenance personnel and improves the processing efficiency when repeated faults occur.

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  • Engineering & Computer Science (AREA)
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  • Computational Linguistics (AREA)
  • Data Mining & Analysis (AREA)
  • General Engineering & Computer Science (AREA)
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  • Probability & Statistics with Applications (AREA)
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Abstract

Un procédé d'analyse de connaissances de fonctionnement et de maintenance à base de technologie à IA comprend les étapes suivantes : S1, la détection, en temps réel et au moyen d'un système de détection, d'un état de fonctionnement d'appareil et des données de charge, et si une défaillance de fonctionnement d'appareil se produit ou qu'une charge devient trop grande, la collection d'un signal de défaillance, et la transmission du signal à un moteur d'analyse à IA; S2, le parsage et l'analyse du signal de défaillance au moyen du moteur d'analyse à IA, et la réalisation, selon un résultat d'analyse, d'une opération de mise en correspondance par rapport à des données de fonctionnement et de maintenance dans une base de données de connaissances; S3, le moteur d'analyse à IA génère une solution de réponse de défaillance, et renvoie la solution de réponse à la base de données de connaissances pour augmenter les données de la base de données de connaissances; S4, une unité d'exécution effectuant un processus de fonctionnement et de maintenance en fonction de la solution de réponse de défaillance; et S5, la génération d'un rapport de fonctionnement et de maintenance après que le processus de fonctionnement et de maintenance est effectué. Lorsque des défaillances répétées se produisent, l'invention utilise le moteur d'analyse à IA pour analyser des informations de défaillance, et sélectionne à son tour, en fonction d'un résultat d'analyse, une solution de réponse correspondante provenant d'une base de données, ce qui permet de réduire la charge de travail du personnel de fonctionnement et de maintenance, et d'améliorer l'efficacité de réponse pour des défaillances répétées.
PCT/CN2020/102157 2020-05-20 2020-07-15 Procédé d'analyse de connaissances de fonctionnement et de maintenance intelligent basé sur la technologie à ia WO2021232567A1 (fr)

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CN115018095A (zh) * 2022-05-26 2022-09-06 平安银行股份有限公司 设备故障处理方法、装置、设备及存储介质
CN116506321A (zh) * 2023-04-28 2023-07-28 杭州富阳海康保泰安防技术服务有限公司 一种基于数据分析的运维智能终端
CN116743603A (zh) * 2023-08-16 2023-09-12 广州海晟科技有限公司 一种私有云平台信息系统安全运维方法和系统
CN116882966A (zh) * 2023-06-27 2023-10-13 广州慧云网络科技有限公司 一种运维设备巡检结果的故障判断方法和装置
CN116932148A (zh) * 2023-09-19 2023-10-24 山东浪潮数据库技术有限公司 一种基于ai的问题诊断系统及方法
CN117033592A (zh) * 2023-08-09 2023-11-10 北京百度网讯科技有限公司 运维处理方法、装置、系统、电子设备及存储介质
CN117650623A (zh) * 2023-11-22 2024-03-05 广东天汇储能科技有限公司 一种基于轻量化大模型的锂电池储能电站运维方法及装置
CN117764422A (zh) * 2024-02-22 2024-03-26 北京洁禹通环保科技有限公司 智慧节能运维管理云平台

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CN113591952A (zh) * 2021-07-19 2021-11-02 湖南汉拓物联科技有限公司 基于物联网数据流的人工智能运维系统及方法
CN114710391B (zh) * 2022-03-22 2023-06-23 中国电子科技集团公司第五十四研究所 一种适用于专用通信系统的智能化故障感知分析处理方法
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CN115858324B (zh) * 2023-02-02 2023-05-12 北京神州光大科技有限公司 基于ai的it设备故障处理方法、装置、设备和介质
CN117952022A (zh) * 2024-03-26 2024-04-30 杭州广立微电子股份有限公司 良率多维度互动系统、方法、计算机设备和存储介质

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CN115018095A (zh) * 2022-05-26 2022-09-06 平安银行股份有限公司 设备故障处理方法、装置、设备及存储介质
CN116506321A (zh) * 2023-04-28 2023-07-28 杭州富阳海康保泰安防技术服务有限公司 一种基于数据分析的运维智能终端
CN116506321B (zh) * 2023-04-28 2023-11-24 杭州富阳海康保泰安防技术服务有限公司 一种基于数据分析的运维智能终端
CN116882966B (zh) * 2023-06-27 2024-04-19 广东慧云科技股份有限公司 一种运维设备巡检结果的故障判断方法和装置
CN116882966A (zh) * 2023-06-27 2023-10-13 广州慧云网络科技有限公司 一种运维设备巡检结果的故障判断方法和装置
CN117033592A (zh) * 2023-08-09 2023-11-10 北京百度网讯科技有限公司 运维处理方法、装置、系统、电子设备及存储介质
CN116743603B (zh) * 2023-08-16 2023-10-20 广州海晟科技有限公司 一种私有云平台信息系统安全运维方法和系统
CN116743603A (zh) * 2023-08-16 2023-09-12 广州海晟科技有限公司 一种私有云平台信息系统安全运维方法和系统
CN116932148A (zh) * 2023-09-19 2023-10-24 山东浪潮数据库技术有限公司 一种基于ai的问题诊断系统及方法
CN116932148B (zh) * 2023-09-19 2024-01-19 山东浪潮数据库技术有限公司 一种基于ai的问题诊断系统及方法
CN117650623A (zh) * 2023-11-22 2024-03-05 广东天汇储能科技有限公司 一种基于轻量化大模型的锂电池储能电站运维方法及装置
CN117764422A (zh) * 2024-02-22 2024-03-26 北京洁禹通环保科技有限公司 智慧节能运维管理云平台
CN117764422B (zh) * 2024-02-22 2024-04-26 北京洁禹通环保科技有限公司 智慧节能运维管理云平台

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