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Heoncheol Lee,Yongsung Kwon,Kipyo Kim 제어로봇시스템학회 2018 제어로봇시스템학회 국제학술대회 논문집 Vol.2018 No.10
This paper addresses the problem of the embedded system health management for high-speed flight systems. Especially, we focus the variation of power signals used in embedded systems because the electrical degeneration is strongly related to the power levels and frequencies. If the power signals can be classified into normal status and abnormal status, the sudden electrical degeneration of embedded systems can be successfully detected. The conventional threshold-based classification which has been used in aerospace and defense fields cannot find out the hidden anomaly within the thresholds. This paper proposes an accurate power signal classification method using combinational spectrogram-based convolutional neural networks (CNN). The power signals are combined with eigenvalues and converted to spectrogram which can analyze them on time and frequency domain simultaneously. Then, the CNN for power signal classification is trained and validated using the combinational spectrograms. Inference results showed that the proposed method can accurately classify the power signals into normal status and abnormal status.
Average Blurring-based Anomaly Detection for Vision-based Mask Inspection Systems
Hyojin Lee,Heoncheol Lee 제어로봇시스템학회 2021 제어로봇시스템학회 국제학술대회 논문집 Vol.2021 No.10
When facial masks are produced, various types of defects may appear on mask filters. These defects may include the hair of the inspectors and unexpected raw materials in the production processes. This paper proposes a new method for detecting anomaly regardless of the size and shape of defects. The proposed method uses two-step image processing to detect anomaly. The first step is to use Average Blurring on the mask filter image for image blurring. The most important thing in this step is the kernel size of the Average Blurring is increased to extend the pixel value with defects to the surrounding pixels. In the second step, the Pearson correlation coefficient between the normal mask filter image and the input mask filter image is used according to kernel size. The larger the kernel size of Average Blurring, the lower their correlation coefficient. If the correlation coefficient at a particular kernel size is lower than the threshold value, it is decided as defective image.
DSP를 이용한 2㎾급 고효율 Bridgeless PFC Converter
이윤재(Yunjae Lee),유광민(Gwangmin Yoo),신헌철(Heoncheol Shin),고돈열(Donyeol Ko),정호철(Hochul Jung),정유석(Yuseok Jeong),이준영(Junyoung Lee) 전력전자학회 2010 전력전자학술대회 논문집 Vol.2010 No.7
최근 에너지의 근원이 되는 원유가의 급등으로 인해 에너지 소비에 대한 국내외적인 관심이 증폭되어 에너지를 소비하는 측의 효율개선에 대한 요구가 급등하고 있으며 전력변환기 시장에서도 효율이 전력변환기의 사용자의 선택기준이 될 정도로 매우 강력한 실정이다. 본 논문에서는 DSP(TMS320F28035)를 이용한 2kW급 고효율 Bridgeless PFC Converter를 제안한다. 제안된 Converter를 실험을 통해 고효율과 고전력밀도의 기능을 검증하였다.