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JRM Vol.7 No.3 pp. 225-229
doi: 10.20965/jrm.1995.p0225
(1995)

Paper:

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Inspection System of Soldering Joint on Printed Circuit Board by Using Neural Network

Shunichiro Oe*, Kennichi Kaida**, Daisuke Nagai**,
Mituo Nakamura**, Tomohiro Kimura** and Koichi Kameyama**

*Faculty of Engineering, University of Tokushima, 2-1 Minamijosanjima, Tokushima, 770 Japan

**Matsushita Kotobuki Electronic Ind. Co., Ltd., Kawauchi-cho, Onsen-gun, Ehime, 791-03 Japan

Received:
February 3, 1995
Accepted:
February 17, 1995
Published:
June 20, 1995
Creative Commons License
Keywords:
Inspection system, Printed circuit board, Soldering joint, Feature extraction, Neural network
Abstract

This paper deals with a new inspection system of soldering joint on printed circuit board by using neural network. A sensor unit of this system consists of a semiconductor laser unit, four PSDs, and a pin photo-diode. We can obtain four types of images which are called height image, PSD brightness image, vertical image and vector image, by using four sensor units. We extract the features which show the state of soldering joint from these images and develop an inspection system using the neural networks constructed for the features and the state of soldering joint.

Cite this article as:
S. Oe, K. Kaida, D. Nagai, <. Nakamura, T. Kimura, and K. Kameyama, “Inspection System of Soldering Joint on Printed Circuit Board by Using Neural Network,” J. Robot. Mechatron., Vol.7, No.3, pp. 225-229, 1995.
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