Aircraft sensor fault diagnosis based on Kalman filter innovation sequence

Author

Caliskan, Fikret ; Hajiyev, Chingiz M.

Author_Institution

Fac. Electr. Eng., Istanbul Tech. Univ., Turkey

Volume

2

fYear

1998

fDate

16-18 Dec 1998

Firstpage

1313

Abstract

Methods of testing the agreement between the innovation sequence and white noise, and the detection of any change of its mathematical expectation have been discussed by Willsky (1976) and Himmelblau (1978). In this paper a novel approach based on the innovation sequence of Kalman filter is introduced for fault detection and isolation, and the method is applied to an aircraft model. The faults are assumed as changes in the covariance matrix of the sensor measurements of the aircraft. There is no real-time method for detecting faults affecting the covariance matrix. The method presented in this paper can quickly detect that type of faults

Keywords

Kalman filters; aircraft instrumentation; covariance matrices; fault diagnosis; sensors; Kalman filter; aircraft; covariance matrix; fault detection; fault diagnosis; fault isolation; innovation sequence; sensors; Aircraft propulsion; Covariance matrix; Electrical fault detection; Equations; Fault detection; Fault diagnosis; Gyroscopes; Technological innovation; Testing; White noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1998. Proceedings of the 37th IEEE Conference on

Conference_Location

Tampa, FL

ISSN

0191-2216

Print_ISBN

0-7803-4394-8

Type

conf

DOI

10.1109/CDC.1998.758463

Filename

758463