Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Multiple fault-based FDI and reconfiguration for aircraft engine sensors

Multiple fault-based FDI and reconfiguration for aircraft engine sensors PurposeCondition monitoring and health management of an aircraft engine is of importance due to engine’s critical position in aircraft. Missions require uninterrupted and safer conditions during the flight or taxi operations. Hence, the deviations, abnormal situations or failures have to be under control. This paper aims to propose a cascade connected approach for an aircraft engine fault tolerant control.Design/methodology/approachThe cascade connected structure includes a full-order unknown input observer for fault detection and eliminating the unknown disturbance effect on system, a generalized observer scheme for fault isolation and a Boolean logic mechanism for decision-making in reconfiguration process, respectively. This combination is simulated on a linear turbojet engine model in case of unknown input disturbance and under various sensor failure scenarios.FindingsThe simulation results show that the suggested fault detection isolation reconfiguration (FDIR) approach works effectively for multiple sensor failures with various amplitudes.Originality/valueDifferent from other studies, the proposed model is sensitive to unknown input disturbance and failures that have unknown amplitudes. One another notable feature of suggested FDIR approach is adaptability of structure against multiple sensor failures. Here, it is assumed that only a single fault is to be detected and isolated at a time. The simulation results show that the proposed structure can be suggested for linear models especially for physical redundancy-based real-time applications easily, quickly and effectively. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Aircraft Engineering and Aerospace Technology: An International Journal Emerald Publishing

Multiple fault-based FDI and reconfiguration for aircraft engine sensors

Loading next page...
 
/lp/emerald-publishing/multiple-fault-based-fdi-and-reconfiguration-for-aircraft-engine-GWYGOvE7Hs

References (17)

Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
1748-8842
DOI
10.1108/AEAT-04-2015-0100
Publisher site
See Article on Publisher Site

Abstract

PurposeCondition monitoring and health management of an aircraft engine is of importance due to engine’s critical position in aircraft. Missions require uninterrupted and safer conditions during the flight or taxi operations. Hence, the deviations, abnormal situations or failures have to be under control. This paper aims to propose a cascade connected approach for an aircraft engine fault tolerant control.Design/methodology/approachThe cascade connected structure includes a full-order unknown input observer for fault detection and eliminating the unknown disturbance effect on system, a generalized observer scheme for fault isolation and a Boolean logic mechanism for decision-making in reconfiguration process, respectively. This combination is simulated on a linear turbojet engine model in case of unknown input disturbance and under various sensor failure scenarios.FindingsThe simulation results show that the suggested fault detection isolation reconfiguration (FDIR) approach works effectively for multiple sensor failures with various amplitudes.Originality/valueDifferent from other studies, the proposed model is sensitive to unknown input disturbance and failures that have unknown amplitudes. One another notable feature of suggested FDIR approach is adaptability of structure against multiple sensor failures. Here, it is assumed that only a single fault is to be detected and isolated at a time. The simulation results show that the proposed structure can be suggested for linear models especially for physical redundancy-based real-time applications easily, quickly and effectively.

Journal

Aircraft Engineering and Aerospace Technology: An International JournalEmerald Publishing

Published: May 2, 2017

There are no references for this article.