Visual solder inspection using neural network
作者:
Yukichi Koji,
Naoyoshi Takatsu,
Masanari Oh,
期刊:
Systems and Computers in Japan
(WILEY Available online 1996)
卷期:
Volume 27,
issue 1
页码: 92-100
ISSN:0882-1666
年代: 1996
DOI:10.1002/scj.4690270109
出版商: Wiley Subscription Services, Inc., A Wiley Company
关键词: Neural network;solder;visual inspection;feature extraction;image recognition
数据来源: WILEY
摘要:
AbstractThis paper proposes a method optically to inspect the state of each soldered lead of a semiconductor package. The surface of the soldered lead is recorded using a CCD camera from a direction perpendicular to it and illuminated from the same direction as the camera. The features of the pattern and the distribution of the brightness on soldered lead are extracted from the recorded image, so that the quality of the soldering is judged from them. It has already been proven that the method is effective to inspect bumps on a soldered part. This paper proves experimentally that the method is also effective to inspect soldered leads. The images of soldered leads have more variations than those of bumps. Therefore, the determination of condition that correctly represent the features and sections of an image is the key in this experiment. After the best conditions have been found, the experimental results using 508 samples (including 175 defective samples) show a 100 percent detection rate for defective samples and 95.7 percent of normal solderings. These results agree with those gained from human visual inspections.
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