Research on Fault Diagnosis of Aircraft with Wing Damage Based on Unscented Kalman Filter

Lei Wang, Xiaoxiong Liu, Yu Li, Kecheng Li, Ruichen Ming

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The severe asymmetric wing damage poses a significant threat to the safety of the flight. To improve the accuracy of damaged aircraft diagnoses, this paper designs a fault diagnosis system based on the Unscented Kalman Filter for wing-damaged aircraft. First, a variable center-of-gravity wing-damaged aircraft model is established by using the non-center of mass method. Then, the Unscented Kalman Filters are designed for the aircraft under the normal and wing damage conditions respective, and the probability of faults is calculated through the Bayesian posterior criterion. Finally, the effectiveness of designed fault diagnosis system is demonstrated, whose results show that it has high accuracy and real-time performance and can achieve satisfied fault diagnosis effects.

Original languageEnglish
Title of host publication2023 42nd Chinese Control Conference, CCC 2023
PublisherIEEE Computer Society
Pages5021-5026
Number of pages6
ISBN (Electronic)9789887581543
DOIs
StatePublished - 2023
Event42nd Chinese Control Conference, CCC 2023 - Tianjin, China
Duration: 24 Jul 202326 Jul 2023

Publication series

NameChinese Control Conference, CCC
Volume2023-July
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference42nd Chinese Control Conference, CCC 2023
Country/TerritoryChina
CityTianjin
Period24/07/2326/07/23

Keywords

  • Aircraft Modeling
  • Bayesian Posterior Estimation
  • Fault Diagnosis
  • Unscented Kalman Filter
  • Wing Damage

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