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

Learn More →

EMMAE failure detection system and failure evaluation over flight performance

EMMAE failure detection system and failure evaluation over flight performance Purpose – The purpose of this paper is to present the research into fault detection and isolation (FDI) and evaluation of the reduction of performance after failures occurred in the flight control system (FCS) during its mission operation. Design/methodology/approach – The FDI is accomplished via using the multiple models scheme which is developed based on the Extend Kalman Filter (EKF) algorithm. Towards this objective, the healthy mode of the FCS under different type of failures, including the control surfaces and structural, should be considered. It developed a bank of extended multiple models adaptive estimation (EMMAE) to detect and isolate the above mentioned failures in the FCS. In addition, the performances including the flight envelope, the voyage and endurance in cruising are proposed to reference and evaluate the process of mission, especially for UAV under failure conditions. Findings – The contribution of this paper is to provide the information not only about the failures, but also considering whether the UAV can accomplish the task for the ground station. Originality/value – The main contribution of this paper is in the areas of the structural and control surface faults researching, which are occurred in the mission procedures and emphasized the identification of those failures' magnitudes. The FDI scheme includes the performance evaluation, while the evaluation obtained through the extensive numerical simulations and saved in the offline database. As a consequence, it is more accurate and less computationally demanding while evaluating the performance. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Intelligent Computing and Cybernetics Emerald Publishing

EMMAE failure detection system and failure evaluation over flight performance

Loading next page...
 
/lp/emerald-publishing/emmae-failure-detection-system-and-failure-evaluation-over-flight-A0u0y00p8J
Publisher
Emerald Publishing
Copyright
Copyright © 2012 Emerald Group Publishing Limited. All rights reserved.
ISSN
1756-378X
DOI
10.1108/17563781211255916
Publisher site
See Article on Publisher Site

Abstract

Purpose – The purpose of this paper is to present the research into fault detection and isolation (FDI) and evaluation of the reduction of performance after failures occurred in the flight control system (FCS) during its mission operation. Design/methodology/approach – The FDI is accomplished via using the multiple models scheme which is developed based on the Extend Kalman Filter (EKF) algorithm. Towards this objective, the healthy mode of the FCS under different type of failures, including the control surfaces and structural, should be considered. It developed a bank of extended multiple models adaptive estimation (EMMAE) to detect and isolate the above mentioned failures in the FCS. In addition, the performances including the flight envelope, the voyage and endurance in cruising are proposed to reference and evaluate the process of mission, especially for UAV under failure conditions. Findings – The contribution of this paper is to provide the information not only about the failures, but also considering whether the UAV can accomplish the task for the ground station. Originality/value – The main contribution of this paper is in the areas of the structural and control surface faults researching, which are occurred in the mission procedures and emphasized the identification of those failures' magnitudes. The FDI scheme includes the performance evaluation, while the evaluation obtained through the extensive numerical simulations and saved in the offline database. As a consequence, it is more accurate and less computationally demanding while evaluating the performance.

Journal

International Journal of Intelligent Computing and CyberneticsEmerald Publishing

Published: Aug 17, 2012

Keywords: Fault detection and isolation (FDI); Extend Kalman Filter (EKF); Extended multiple models adaptive estimation (EMMAE); Flight envelope; UAV; Flight control; Flight operations; Failure (mechanical)

References