Recognition and detection methods in supervision and control of the manufacturing processes

Author

Shpilewski, E.

Author_Institution

Inst. of Math. & Inf., Acad. of Sci., Vilnius, Lithuania

Volume

3

fYear

2000

fDate

2000

Firstpage

2067

Abstract

The paper considers a new approach to the supervision and control of the manufacturing processes. It treats supervision and control of the manufacturing systems as a problem of discrete status, operating conditions and events of dynamic objects recognition. The software of computer aided systems for the manufacturing systems supervision includes tools for output signals clustering, dynamic models of discrete status identification, parameters of dynamic models for each status estimation, observable realisation classification and decision making. A method of diagnostics of the electric engine status based on the analysis of process realisation that takes place in the engine is described

Keywords

fault diagnosis; manufacturing processes; object recognition; parameter estimation; pattern classification; production control; fault detection; fault diagnosis; identification; manufacturing processes; objects recognition; parameter estimation; pattern classification; signals clustering; supervision; Bayesian methods; Control systems; Engines; Equations; Informatics; Manufacturing processes; Manufacturing systems; Mathematics; Object recognition; Random processes;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference, 2000. Proceedings of the 2000

Conference_Location

Chicago, IL

ISSN

0743-1619

Print_ISBN

0-7803-5519-9

Type

conf

DOI

10.1109/ACC.2000.879565

Filename

879565