Optimal sequence planning for automobile gauge panel image inspection

Author

Liu, Shuguang ; Liu, Mingyuan ; Wang, Dongwen

Author_Institution

Sch. of Electron. & Inf., Xi´´an Polytech. Univ., Xi´´an

fYear

2008

fDate

10-12 Oct. 2008

Firstpage

1173

Lastpage

1176

Abstract

An optimal inspection sequence planning method in spot-check of gauge panel is studied in this paper. Experiments using Hopfield neural network is carried out and a new method combining global planning with local complete searching is put forward. On the basis of the research works above, a machine vision inspection system for automobile gauge panel is successfully developed. It is used in the automobile assemble line, performing quality inspection task with good optimal solution for random distributed points with a fairly large number.

Keywords

Hopfield neural nets; assembling; automotive components; image sequences; inspection; production engineering computing; production planning; Hopfield neural network; automobile assemble line; automobile gauge panel image inspection; machine vision inspection system; optimal inspection sequence planning method; quality inspection task; random distributed points; Assembly; Automatic control; Automobiles; Cameras; Computer errors; Computer numerical control; Hopfield neural networks; Inspection; Machine vision; Petroleum; Machine vision; gauge panel; inspection; optimization; sequence planning;

fLanguage

English

Publisher

ieee

Conference_Titel

System Simulation and Scientific Computing, 2008. ICSC 2008. Asia Simulation Conference - 7th International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4244-1786-5

Electronic_ISBN

978-1-4244-1787-2

Type

conf

DOI

10.1109/ASC-ICSC.2008.4675544

Filename

4675544