Anomaly detection of solder joint on print circuit board by using Adversarial Autoencoder

Keisuke Goto; Kunihito Kato; Shunsuke Nakatsuka; Takaho Saito; Hiroaki Aizawa

doi:10.1117/12.2521762

16 July 2019 Anomaly detection of solder joint on print circuit board by using Adversarial Autoencoder

Keisuke Goto, Kunihito Kato, Shunsuke Nakatsuka, Takaho Saito, Hiroaki Aizawa

Proceedings Volume 11172, Fourteenth International Conference on Quality Control by Artificial Vision; 111720T (2019) https://doi.org/10.1117/12.2521762
Event: Fourteenth International Conference on Quality Control by Artificial Vision, 2019, Mulhouse, France

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.

Citation Download Citation

Keisuke Goto, Kunihito Kato, Shunsuke Nakatsuka, Takaho Saito, and Hiroaki Aizawa "Anomaly detection of solder joint on print circuit board by using Adversarial Autoencoder", Proc. SPIE 11172, Fourteenth International Conference on Quality Control by Artificial Vision, 111720T (16 July 2019); https://doi.org/10.1117/12.2521762

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