Failure diagnosis using the state chi-square test and the ARTMAP neural networks

Author

Da, Ren ; Ching-Fang Lin

Author_Institution

American GNC Corp., Chatsworth, CA, USA

Volume

5

fYear

1995

fDate

21-23 Jun 1995

Firstpage

3279

Abstract

A failure diagnosis scheme using the state chi-square test and the ARTMAP neural network techniques is presented for dynamic systems. After a failure is detected by the state chi-square test, two ARTMAP neural networks are applied to recognize patterns formed by data of the state chi-square test in order to determine when the failure happens, how serious the failure is, and where the failure is located. The efficacy of the proposed scheme is demonstrated by simulation examples where soft failures in a GPS/SDINS (Global Positioning System/Strapdown Inertial Navigation System) integrated navigation system are successfully diagnosed

Keywords

ART neural nets; fault diagnosis; pattern recognition; state estimation; ARTMAP neural networks; GPS/SDINS integrated navigation system; Global Positioning System; Strapdown Inertial Navigation System; failure diagnosis; state chi-square test; Accelerometers; Condition monitoring; Error correction; Global Positioning System; Inertial navigation; Neural networks; Pattern recognition; Sensor systems; State estimation; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference, Proceedings of the 1995

Conference_Location

Seattle, WA

Print_ISBN

0-7803-2445-5

Type

conf

DOI

10.1109/ACC.1995.532209

Filename

532209