• Macromolecular Research
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• 제17권11호
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• pp.863-869
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• 2009

The effect of a multiwalled carbon nanotube (MWCNT) dispersion on the electrical, morphological and rheological properties of polycarbonate (PC)/MWCNT composites was investigated, with and without pretreating the MWCNTs with hydrogen peroxide oxidation and lyophilization. The resulting PC/treated MWCNT composites showed higher electrical conductivity than the PC/untreated MWCNT composites. The morphological behavior indicated the treated composites to have greater dispersion of MWCNTs in the PC matrix. In addition, the electromagnetic interference shielding efficiency (EMI SE) of the treated composites was higher than that of the untreated ones. Rheological studies of the composites showed that the complex viscosity of the treated composites was higher than the untreated ones due to increased dispersion of the MWCNTs in the PC matrix, which is consistent with the electrical conductivity, EMI SE and morphological studies of the treated composites. The latter results suggested that the increased electrical conductivity and EMI SE of the treated composites were mainly due to the increased dispersion of MWCNTs in the PC matrix.

• 항공우주시스템공학회지
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• 제17권1호
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• pp.68-78
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• 2023

본 논문에서는 항공기 내의 RF 방사 신호로 인하여 비상 유압 경고등이 비정상으로 점등되는 현상에 대한 개선 방안을 연구하였다. RF 방사 신호의 전자파 간섭으로 비행 중에 비상 유압 시스템의 경고등이 점등되면, 비행 임무 및 안전에 영향을 주어 비행 임무의 효율 저해 및 정비 소요가 발생한다. 따라서, 비상 유압 경고등의 비정상 점등에 대해서 원인 분석 및 고장탐구를 수행하였다. RF 방사 신호의 경로에 있는 항공기의 동체 하부 복합체 스트립을 차폐하여 비상유입지시계로 유입되는 RF 방사 신호를 차단하도록 개선하였다. 또한, 지상과 비행 모니터링을 통해 개선 방안을 적용한 결과도 함께 기술하였다.

• 한국산업융합학회 논문집
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• 제24권6_2호
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• pp.729-735
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• 2021

Recently Artificial Intelligence(AI) has been developed and used in various fields. Especially AI recognition technology can perceive and distinguish images so it should plays a significant role in quality inspection process. For stability of autonomous driving technology, semiconductors inside automobiles must be protected from external electromagnetic wave(EM wave). As a shield film, a thin polymeric material with hole shaped micro-patterns created by a laser processing could be used for the protection. The shielding efficiency of the film can be increased by the hole structure with appropriate pitch and size. However, since the sensitivity of micro-machining for some parameters, the shape of every single hole can not be same, even it is possible to make defective patterns during process. And it is absolutely time consuming way to inspect all patterns by just using optical microscope. In this paper, we introduce a AI inspection system which is based on web site AI tool. And we evaluate the usefulness of AI model by calculate Area Under ROC curve(Receiver Operating Characteristics). The AI system can classify the micro-patterns into normal or abnormal ones displaying the text of the result on real-time images and save them as image files respectively. Furthermore, pressing the running button, the Hardware of robot arm with two Arduino motors move the film on the optical microscopy stage in order for raster scanning. So this AI system can inspect the entire micro-patterns of a film automatically. If our system could collect much more identified data, it is believed that this system should be a more precise and accurate process for the efficiency of the AI inspection. Also this one could be applied to image-based inspection process of other products.