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Proceedings Paper

Anomaly detection of solder joint on print circuit board by using Adversarial Autoencoder
Author(s): Keisuke Goto; Kunihito Kato; Shunsuke Nakatsuka; Takaho Saito; Hiroaki Aizawa
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Paper Abstract

We propose a defect detection method of solders on a printed circuit board using X-ray CT inspection system and Adversarial Autoencoder (AAE)[1] . We obtain sliced images of the solder using X-ray CT and extract their features that follow the standard normal distribution by using AAE. Then, the solder defects are detected by Hotelling's T square[2]. As a result of experiments, we show that we can classify normal and anomalous data samples completely on the condition of training with large normal samples and small anomalous samples.

Paper Details

Date Published: 16 July 2019
PDF: 6 pages
Proc. SPIE 11172, Fourteenth International Conference on Quality Control by Artificial Vision, 111720T (16 July 2019); doi: 10.1117/12.2521762
Show Author Affiliations
Keisuke Goto, Gifu Univ. (Japan)
Kunihito Kato, Gifu Univ. (Japan)
Shunsuke Nakatsuka, Gifu Univ. (Japan)
Takaho Saito, Aisin AW Co., Ltd. (Japan)
Hiroaki Aizawa, Gifu Univ. (Japan)


Published in SPIE Proceedings Vol. 11172:
Fourteenth International Conference on Quality Control by Artificial Vision
Christophe Cudel; Stéphane Bazeille; Nicolas Verrier, Editor(s)

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