With the rapid development of network technology, computer resources, including server resources, have shown a trend of high concentration, multiple devices, and multiple types. As a result, various types of server failures occur frequently, not only for basic monitoring software monitoring services. It puts forward higher requirements and has higher strength in the timeliness and accuracy of sending alarm information. Therefore, it is necessary to converge and analyze the alarm information and give expert-level solutions to the fault information. This article first designed the monitoring and alarm module using the flask framework to enable it to receive alarm information uniformly, converge and merge the alarm information, and use the Vue framework to display the alarm information on the page. Then, use the Python PyCLIPS library based on CLIPS to build the inference engine of the server fault diagnosis expert system. Finally use the “production rules” expert system knowledge expression to complete the construction of the knowledge base.


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    Titel :

    Research on Server Fault Diagnosis Based on Expert System


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Wang, Yi (Herausgeber:in) / Martinsen, Kristian (Herausgeber:in) / Yu, Tao (Herausgeber:in) / Wang, Kesheng (Herausgeber:in) / Zhou, Chuanhong (Autor:in) / Guo, Daohao (Autor:in) / Zhang, Chong (Autor:in)

    Kongress:

    International Workshop of Advanced Manufacturing and Automation ; 2020 ; Zhanjiang, China October 12, 2020 - October 13, 2020



    Erscheinungsdatum :

    23.01.2021


    Format / Umfang :

    8 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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