• 한국재료학회지
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• 제18권10호
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• pp.558-563
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• 2008

TiAlN films were deposited on WC-5Co substrates with different buffer layers by D.C. magnetron sputtering. The films were evaluated by microstructural observations and measuring of preferred orientation, hardness value, and adhesion force. As a process variable, various buffer layers were used such as TiAlN single layer, TiAlN/TiAl, TiAlN/TiN and TiAlN/CrN. TiAlN coating layer showed columnar structures which grew up at a right angle to the substrates. The thickness of the TiAlN coating layer was about $1.8{\mu}m$, which was formed for 200 minutes at $300^{\circ}$. XRD analysis showed that the preferred orientation of TiAlN layer with TiN buffer layer was (111) and (200), and the specimens of TiAlN/TiAl, TiAlN/CrN, TiAlN single layer have preferred orientation of (111), respectively. TiAlN single layer and TiAlN/TiAl showed good adhesion properties, showing an over 80N adhesion force, while TiAlN/TiN film showed approximately 13N and the TiAlN/CrN was the worst case, in which the layer was destroyed because of high internal residual stress. The value of micro vickers hardness of the TiAlN single layer, TiAlN/TiAl and TiAlN/TiN layers were 2711, 2548 and 2461 Hv, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권6호
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• pp.2168-2187
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• 2021

The smart grid replaces the traditional power structure with information inventiveness that contributes to a new physical structure. In such a field, malicious information injection can potentially lead to extreme results. Incorrect, FDI attacks will never be identified by typical residual techniques for false data identification. Most of the work on the detection of FDI attacks is based on the linearized power system model DC and does not detect attacks from the AC model. Also, the overwhelming majority of current FDIA recognition approaches focus on FDIA, whilst significant injection location data cannot be achieved. Building on the continuous developments in deep learning, we propose a Deep Learning based Locational Detection technique to continuously recognize the specific areas of FDIA. In the development area solver gap happiness is a False Data Detector (FDD) that incorporates a Convolutional Neural Network (CNN). The FDD is established enough to catch the fake information. As a multi-label classifier, the following CNN is utilized to evaluate the irregularity and cooccurrence dependency of power flow calculations due to the possible attacks. There are no earlier statistical assumptions in the architecture proposed, as they are "model-free." It is also "cost-accommodating" since it does not alter the current FDD framework and it is only several microseconds on a household computer during the identification procedure. We have shown that ANN-MLP, SVM-RBF, and CNN can conduct locational detection under different noise and attack circumstances through broad experience in IEEE 14, 30, 57, and 118 bus systems. Moreover, the multi-name classification method used successfully improves the precision of the present identification.

• 한국표면공학회지
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• 제46권2호
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• pp.68-74
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• 2013

For the coating of diamond films on WC-Co tools, a buffer interlayer is needed because Co catalyzes diamond into graphite. W and Ti were chosen as candidate interlayer materials to prevent the diffusion of Co during diamond deposition. W or Ti interlayer of $1{\mu}m$ thickness was deposited on WC-Co substrate under Ar in a DC magnetron sputter. After seeding treatment of the interlayer-deposited specimens in an ultrasonic bath containing nanometer diamond powders, $2{\mu}m$ thick nanocrystalline diamond (NCD) films were deposited at $600^{\circ}C$ over the metal layers in a 2.45 GHz microwave plasma CVD system. The cross-sectional morphology of films was observed by FESEM. X-ray diffraction and visual Raman spectroscopy were used to confirm the NCD crystal structure. Micro hardness was measured by nano-indenter. The coefficient of friction (COF) was measured by tribology test using ball on disk method. After tribology test, wear tracks were examined by optical microscope and alpha step profiler. Rockwell C indentation test was performed to characterize the adhesion between films and substrate. Ti and W were found good interlayer materials to act as Co diffusion barriers and diamond nucleation layers. The COFs on NCD films with W or Ti interlayer were measured as less than 0.1 whereas that on bare WC-Co was 0.6~1.0. However, W interlayer exhibited better results than Ti in terms of the adhesion to WC-Co substrate and to NCD film. This result is believed to be due to smaller difference in the coefficients of thermal expansion of the related films in the case of W interlayer than Ti one. By varying the thickness of W interlayer as 1, 2, and $4{\mu}m$ with a fixed $2{\mu}m$ thick NCD film, no difference in COF and wear behavior but a significant change in adhesion was observed. It was shown that the thicker the interlayer, the stronger the adhesion. It is suggested that thicker W interlayer is more effective in relieving the residual stress of NCD film during cooling after deposition and results in stronger adhesion.

• 한국자기학회지
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• 제11권5호
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• pp.232-238
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• 2001

Nano결정립 N $d_2$F $e_{14}$B+F $e_3$B 복합상 자성 압분체의 탈자화 현상을 자기특성 변화 및 $\delta$M측정에 의해 분석하였다. 초기 조성 N $d_4$F $e_{73.5}$ $Co_3$H $f_{0.5}$G $a_{0.5}$ $B_{18.5}$의 최대자기에너지적은 리본상태에서 14 MGOe, 분말 압분체에서 6.5 MGOe로 크게 감소하였다. 이러한 현상은 복합상의 리본상태에서 존재하는 교환상호작용력이 분말 압분체에서는 나타나지 않고, 정자장 작용에 의한 탈자화로 인해 잔류자속밀도가 크게 감소한 결과이다. 이는 급냉리본(bulk) 보다 압분체상태에서 정자장 상호작용력이 교환상호작용력보다 더 크게 작용하는 결과로 해석된다. 또한, 자성체 리본을 분쇄하는 과정에서 발생한 응력도 자기특성을 감소시키는 요소임을 확인하였다.하였다.하였다.