2005Unpublished venueRequires access

In-flight fault detection and isolation in aircraft flight control systems

Md. Shafiul Azam, Krishna R. Pattipati, J. Allanach, Scott Poll, A. Patterson-Hine

Open publisher page 48 citations

Abstract

In this paper we consider the problem of test design for real-time fault detection and isolation (FDI) in the flight control system of fixed-wing aircraft. We focus on the faults that are manifested in the control surface elements (e.g., aileron, elevator, rudder and stabilizer) of an aircraft. For demonstration purposes, we restrict our focus on the faults belonging to nine basic fault classes. The diagnostic tests are performed on the features extracted from fifty monitored system parameters. The proposed tests are able to uniquely isolate each of the faults at almost all severity levels. A neural network-based flight control simulator, FLTZreg, is used for the simulation of various faults in fixed-wing aircraft flight control systems for the purpose of FDI

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What this paper is about

In this paper we consider the problem of test design for real-time fault detection and isolation (FDI) in the flight control system of fixed-wing aircraft. We focus on the faults that are manifested in the control surface elements (e.g., aileron, elevator, rudder and stabilizer) of an aircraft. For demonstration purposes, we restrict our focus on the faults belonging to nine basic fault classes. The diagnostic tests are performed on the features extracted from fifty monitored system parameters. The proposed tests are able to uniquely isolate each of the faults at almost all severity levels. A neural network-based flight control simulator, FLTZreg, is used for the simulation of various faults in fixed-wing aircraft flight control systems for the purpose of FDI

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OpenAlex reports 48 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

In this paper we consider the problem of test design for real-time fault detection and isolation (FDI) in the flight control system of fixed-wing aircraft. We focus on the faults that are manifested in the control surface elements (e.g., aileron, elevator, rudder and stabilizer) of an aircraft. For demonstration purposes, we restrict our focus on the faults belonging to nine basic fault classes. The diagnostic tests are performed on the features extracted from fifty monitored system parameters. The proposed tests are able to uniquely isolate each of the faults at almost all severity levels. A neural network-based flight control simulator, FLTZreg, is used for the simulation of various faults in fixed-wing aircraft flight control systems for the purpose of FDI

Key concepts: Aileron, Rudder, Elevator, Flight test, Fault detection and isolation, Flight control surfaces, Flight simulator, Fault (geology)

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