An evidential reasoning extension to quantitative model-based failure diagnosis

Author

Gertler, Janos J. ; Anderson, Kenneth C.

Author_Institution

Dept. of Electr. Eng., George Mason Univ., Fairfax, VA, USA

Volume

22

Issue

2

fYear

1992

Firstpage

275

Lastpage

289

Abstract

The detection and diagnosis of failures in physical systems characterized by continuous-time operation are studied. A quantitative diagnostic methodology has been developed that utilizes the mathematical model of the physical system. On the basis of the latter, diagnostic models are derived each of which comprises a set of orthogonal parity equations. To improve the robustness of the algorithm, several models may be used in parallel, providing potentially incomplete and/or conflicting inferences. Dempster´s rule of combination is used to integrate evidence from the different models. The basic probability measures are assigned utilizing quantitative information extracted from the mathematical model and from online computation performed therewith

Keywords

cognitive systems; failure analysis; inference mechanisms; planning (artificial intelligence); probability; Dempster´s rule; continuous-time operation; diagnostic models; evidential reasoning extension; model-based failure diagnosis; orthogonal parity equations; probability measures; robustness; Chemical industry; Data mining; Equations; Fires; Inference algorithms; Joining processes; Mathematical model; Performance evaluation; Robustness; System testing;

fLanguage

English

Journal_Title

Systems, Man and Cybernetics, IEEE Transactions on

Publisher

ieee

ISSN

0018-9472

Type

jour

DOI

10.1109/21.148430

Filename

148430