{"title":"Research on Fault Diagnosis System Based on Aeroengine Knowledge Base","authors":"Yun Wang, Hua Ming, Guigang Zhang, Xing Ai, Fujian Xu, Benwang Li","doi":"10.1109/phm-yantai55411.2022.9942160","DOIUrl":null,"url":null,"abstract":"This paper studies the fault diagnosis system based on the aeroengine knowledge base, which covers the historical fault data, fault mode data, fault characteristic data of turboshaft/turboprop aero-engine, as well as diagnostic reasoning composed of expert knowledge base and decision rule base. In practical applications, it can assist the crew to troubleshoot the engine. In the current maintenance work, the troubleshooting of the engine is carried out by the maintenance personnel relying on the accumulated experience. With the accumulation of experience, the accuracy of troubleshooting is gradually improved. However, the sharing of personal experiences is poor. With the update of maintenance personnel, the maintenance capability will be reduced and the knowledge wealth will be wasted. The expert system can store and manage these experiences, to quickly realize the aero-engine fault diagnosis.","PeriodicalId":315994,"journal":{"name":"2022 Global Reliability and Prognostics and Health Management (PHM-Yantai)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 Global Reliability and Prognostics and Health Management (PHM-Yantai)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/phm-yantai55411.2022.9942160","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper studies the fault diagnosis system based on the aeroengine knowledge base, which covers the historical fault data, fault mode data, fault characteristic data of turboshaft/turboprop aero-engine, as well as diagnostic reasoning composed of expert knowledge base and decision rule base. In practical applications, it can assist the crew to troubleshoot the engine. In the current maintenance work, the troubleshooting of the engine is carried out by the maintenance personnel relying on the accumulated experience. With the accumulation of experience, the accuracy of troubleshooting is gradually improved. However, the sharing of personal experiences is poor. With the update of maintenance personnel, the maintenance capability will be reduced and the knowledge wealth will be wasted. The expert system can store and manage these experiences, to quickly realize the aero-engine fault diagnosis.