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RISS 인기검색어
- 검색키워드
- 저자 : Ichiro Omura (검색결과 5 건)
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Determination of Abnormality of IGBT Images Using VGG16
Toui Ogawa,Akihiko Watanabe,Ichiro Omura,Tohru Kamiya 제어로봇시스템학회 2021 제어로봇시스템학회 국제학술대회 논문집 Vol.2021 No.10
A power device is a semiconductor device for power control used for power conversion such as converting direct current to alternating current and alternating current to direct current. It is widely used such as refrigerators, air conditioners which is implemented electronic components that are closely related to our daily lives. Therefore, high reliability and safety are required, and power cycle tests are conducted for the purpose of evaluating them. In the conventional test, there is a problem that it is difficult to perform analysis because sparks are generated during the test and the device is severely damaged after the test. To solve this problem, a new technology has been developed that adds ultrasonic that enable internal observation during the test. However, there are remains a problem that the method for analyzing the ultrasonic image obtained in the new technology has not been established. Also, few abnormal images are obtained in the test. In this paper, we propose a method for detection of abnormal devices based on CNN. Especially, we implement a Cycle-GAN to extend the abnormal data and classify the known image based on improved VGG16. As an experimental result, classification accuracy of = 97.06%, = 93.58%, − = 95.17% were obtained.
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Identification of normal and abnormal from ultrasound images of power devices using VGG16
Toui Ogawa,Humin Lu,Akihiko Watanabe,Ichiro Omura,Tohru Kamiya 제어로봇시스템학회 2020 제어로봇시스템학회 국제학술대회 논문집 Vol.2020 No.10
Power devices are semiconductor devices that handle high voltages and large currents, which are used in electric vehicles, televisions, and trains. Therefore, high reliability and safety are required, and to ensure this, power cycle tests are performed to analyze the breakdown process. Conventional tests are often difficult to analyze due to the influence of sparks generated during the test. Therefore, new tests are being developed by adding ultrasound to conventional methods. The new technology is capable of continuously recording structural changes inside the device during testing, which is expected to make testing much easier than conventional testing. However, the new technology still has some challenges. The main problems are the lack of a method for analyzing large amounts of image data and the extraction of small changes in image features that are difficult to distinguish with the human eye, and the establishment of such a system is required. In this paper, we use deep learning for image classification of the obtained ultrasound images. We propose a new network model with the addition of Batch normalization and Global average pooling to VGG16, which is a pre-trained model. In the experiment, accuracy=98.29%, TPR=98.96% and FPR=7.43% classification accuracy was obtained.
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New Measurement Base De-embedded CPU Load Model for Power Delivery Network Design
Motochika Okano,Koji Watanabe,Masamichi Naitoh,Ichiro Omura 전력전자학회 2015 ICPE(ISPE)논문집 Vol.2015 No.6
CPU load model including on-chip wiring and package interconnection has been required for printed circuit board (PCB) design of digital products according to the improvement in the speed of CPU operation in recent years. Especially, accurate power delivery network (PDN) information inside CPU is indispensable for PCB design according to requirement of low-impedance and the broadband (from DC to GHz) from the inside of CPU to DC-DC converter. While the detailed impedance information inside CPUs is not disclosed to PCB board designers with the complicated back-end and front-end production design for CPU chip and package. This paper aims to establish new methodology to extract CPU load model with combination of measurement and simulation. The method is simple yet powerful for high-end CPU board design.
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Daisuke YUKI,Hyoungseop KIM,Joo Kooi TAN,Seiji ISHIKAWA,Masanori TSUKUDA,Ichiro OMURA 제어로봇시스템학회 2015 제어로봇시스템학회 국제학술대회 논문집 Vol.2015 No.10
Recently, the necessity of environmental regulation, low fuel consumption, and natural energy development is proposed by environmental issues. So the demands of power transistor devices are increased. But measurement technique of the current distribution is not keeping up with further miniaturized and integrated were needed in present condition. Now, therefore, ensuring security attended high functionalization is a subject. IGBT (Insulated Gate Bipolar Transistor) is the device that used for wide range of power devices. So we are developing imaging system used non-contact sensor arrays aimed to IGBT production line. In this paper, we propose a development of a supporting system for visual inspection IGBT device based on statistical feature and complex multi-resolution analysis. First, this performs signal de-noising after entering well-known good data and measured data. Second, the statistical feature is expressed the difference between good data and measured data are calculated. Last, classifying of good and inferiority is performed based on the result of threshold processing. In the paper, we applied our algorithm to 28 sample data including 20 good data and 8 inferiority data.
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