A method of information acquisition and processing for modelling complex production processes

Author

Zhou, Shang-Ming ; Zhang, Xi-Di

Author_Institution

Signal & Commun. Res. Inst., Acad. Sinica, Beijing, China

Volume

1

fYear

1997

fDate

28-31 Oct 1997

Firstpage

805

Abstract

In studies of complex industrial production control systems, especially distributed parameter production processes, it is very difficult to build the strict mathematical model in terms of mechanism analyses. This paper, from the angle of information science, trying to bypass the mechanism analyses, extracts the features of image sequences obtained by the computer vision detection system. It describes the complex industrial production control system by the eigenvectors not the state vectors, which lays the foundations for predicting and judging the working situation or product quality based on a dynamical neural network

Keywords

computer vision; distributed parameter systems; eigenvalues and eigenfunctions; feature extraction; image sequences; neural nets; production control; production engineering computing; complex production process modelling; computer vision; distributed parameter production processes; dynamical neural network; eigenvectors; feature extraction; image sequences; industrial production control systems; information acquisition; information processing; mathematical model; product quality; Data mining; Electrical equipment industry; Image analysis; Image sequence analysis; Industrial control; Information analysis; Information science; Mathematical model; Production control; Production systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Processing Systems, 1997. ICIPS '97. 1997 IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

0-7803-4253-4

Type

conf

DOI

10.1109/ICIPS.1997.672901

Filename

672901