{"title":"Research on Fault Diagnosis Technology of UAV Flight Control System Based on Hybrid Diagnosis Engine","authors":"Mingjie Chen, Jin Yan, Tieying Li, Chengzhi Chi","doi":"10.1109/PHM2022-London52454.2022.00041","DOIUrl":null,"url":null,"abstract":"In order to solve the problem of real-time fault diagnosis of UAV flight control system, a fault diagnosis method based on hybrid diagnosis engine is proposed. Aiming at the multiple fault modes and cross-linking relationships of each node in the flight control system, the system reference model is established by qualitative and quantitative methods, and then a corresponding domain model is established according to the flight control system of a specific model. Finally, the fault diagnosis reasoning engine based on the model and the hybrid diagnosis engine realizes the diagnosis of the current fault of the system. The results show that this method can determine the time and location of the fault in real time and accurately, which provides an effective guarantee for improving the efficiency of UAV fault diagnosis and improving the flight safety of UAV.","PeriodicalId":269605,"journal":{"name":"2022 Prognostics and Health Management Conference (PHM-2022 London)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 Prognostics and Health Management Conference (PHM-2022 London)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PHM2022-London52454.2022.00041","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
In order to solve the problem of real-time fault diagnosis of UAV flight control system, a fault diagnosis method based on hybrid diagnosis engine is proposed. Aiming at the multiple fault modes and cross-linking relationships of each node in the flight control system, the system reference model is established by qualitative and quantitative methods, and then a corresponding domain model is established according to the flight control system of a specific model. Finally, the fault diagnosis reasoning engine based on the model and the hybrid diagnosis engine realizes the diagnosis of the current fault of the system. The results show that this method can determine the time and location of the fault in real time and accurately, which provides an effective guarantee for improving the efficiency of UAV fault diagnosis and improving the flight safety of UAV.