DocumentCode
617944
Title
Detecting PCB component placement defects by genetic programming
Author
Feng Xie ; Uitdenbogerd, Alexandra ; Song, Andrew
Author_Institution
Sch. of Comput. Sci. & IT, RMIT Univ., Melbourne, VIC, Australia
fYear
2013
fDate
20-23 June 2013
Firstpage
1138
Lastpage
1145
Abstract
A novel approach is proposed in this study, which is to evolve visual inspection programs for automatic defect detection on populated printed circuit boards. This GP-based method does not require knowledge of the layout design of a board, nor relevant domain knowledge such as lighting conditions and visual characteristics of the components. Furthermore, conventional image operators are not required to perform the detection. The experiments show that these evolved GP programs can identify all the faults while some suspicious areas are also highlighted. By this GP approach, manual inspection effort can be dramatically reduced. In addition, an evolved GP detection program can readily work on different types of boards without re-training.
Keywords
automatic optical inspection; genetic algorithms; image processing; printed circuit layout; printed circuit manufacture; printed circuit testing; GP approach; GP programs; GP-based method; PCB component placement defect detection; automatic defect detection; genetic programming; image operators; layout design; lighting conditions; manual inspection effort; printed circuit boards; visual characteristics; visual inspection programs; Circuit faults; Educational institutions; Feature extraction; Inspection; Lighting; Printed circuits; Training; automatic optical inspection; defects detection; genetic programming; machine vision; printed circuit board;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation (CEC), 2013 IEEE Congress on
Conference_Location
Cancun
Print_ISBN
978-1-4799-0453-2
Electronic_ISBN
978-1-4799-0452-5
Type
conf
DOI
10.1109/CEC.2013.6557694
Filename
6557694
Link To Document