• 열처리공학회지
• /
• 제12권3호
• /
• pp.215-220
• /
• 1999

Rotary bending fatigue tests were carried out to investigate the artificial defect sensitivity of fatigue limit in annealed and austempered ductile irons. Artificial defect(hole, diameter${\leq}0.4mm$) machined on specimen surface did not bring about an obvious reduction of fatigue limit in austempered ductile iron as compared with annealed. As a result of investigation on $\sqrt{area}$ c which is the critical artificial defect size. $\sqrt{area}$ c of austempered ductile iron is larger than that of annealed. This means that the crack initiation at artificial defect in austempered ductile iron is more difficult in comparison with annealed. In case that the $\sqrt{area}$ c of artificial defect and graphite nodule are same, the rate of crack initiation for graphite nodule is higher than that of artificial defect.

• 대한기계학회논문집A
• /
• 제23권11호
• /
• pp.1922-1928
• /
• 1999

Rotary bending fatigue tests were carried out to investigate the influence of artificial defects on fatigue limit in annealed and austempered ductile iron. Obtained main results are as follows : (1) Artificial defect(micro hole type, dia.<0.4 mm) on specimen surface did not bring about a obvious reduction of fatigue limit in austempered ductile iron(ADI) as compared with annealed ductile iron. (2) According to the investigation of $\sqrt{area}_c$ which is the critical defect size to crack initiation at artificial defect, $\sqrt{area}_c$ of ADI is larger than that of annealed ductile iron. This shows that the situation of crack initiation at artificial defect in ADI is more difficult in comparison with annealed ductile iron. (3) One of the reasons for the low rate of crack initiation from artificial defect in ADI is that the resistance of matrix to crack initiation is higher than that of annealed ductile iron. (4) In case that the $\sqrt{area}$ of artificial defect and graphite nodule is the same, the rate of crack initiation from graphite nodule is higher than that from artificial defect. This reason is that the serious ruggedness around graphite nodule is formed by austempering treatment.

• 한국자동차공학회논문집
• /
• 제7권5호
• /
• pp.221-229
• /
• 1999

We examined the governing factors of fatigue limit in annealed and austempered ductile iron specimens machined micro hole(dia.<0.4mm) in rotary bending fatigue test. Also, the quantitative relationship between fatigue limit and maximum defect size in specimens was investigated. Artificial defect(micro-pit type, dia.<0.4mm) on specimen surface did not bring about an obvious reduction of fatigue limit in austempered ductile iton(ADI) as compared with annealed ductile iron. According to the investigation of ${\sqrt{area}}_c$ which is the critical defect size to crack initiation at artificial defect, ${\sqrt{area}}_c$ of ADI was larger than that of annealed ductile iron. This shows that the situation of crack initiation at artificial defect in ADI is more difficult in comparison with annealed ductile iron. Maximum defect size is one of the important parameters to predict fatigue limit. And, the quantitative relationship, between the fatigue limit ${\sigma}_{\omega}$ and the maximum defect size ${\sqrt{area}}_{max}$ can be expressed to ${\sigma}_{\omega}^n{\cdot}{\sqrt{area}}_{max}=C_2$ where, $C_2$ are constant. Moreover, it is possible to explain the difference in fatigue limit between, austempered and annealed ductile iron by introducing the parameter ${\delta}(=N_{sg}/N_{total})$in a plain spectimen.

• 한국해양공학회지
• /
• 제3권2호
• /
• pp.601-601
• /
• 1989

The behavior of fatigue was studied by using low carbon steel bar with microhole(artificial small defect) under the condition of rotary bending stress which is made artificially at smooth surface and round notch root. The results obtained can be summerized; The behavior of non-propagating cracks which are produced at both tips of small defect occurred to dissymmetry, and it is found to be double size of small defect. For the range of l>lc, threshold stress intensity is constant. However, for the range of l

• 한국해양공학회지
• /
• 제3권2호
• /
• pp.101-107
• /
• 1989

The behavior of fatigue was studied by using low carbon steel bar with microhole(artificial small defect) under the condition of rotary bending stress which is made artificially at smooth surface and round notch root. The results obtained can be summerized; The behavior of non-propagating cracks which are produced at both tips of small defect occurred to dissymmetry, and it is found to be double size of small defect. For the range of l>lc, threshold stress intensity is constant. However, for the range of l

• 한국세라믹학회지
• /
• 제41권5호
• /
• pp.406-409
• /
• 2004

교류 구동 분산형 EL(ACPEL)에 사용되는 ZnS:Cu 청색 형광체를 고상 반응법으로 제조하였다. 1차 소성 후 인위적 결함을 형광체 표면에 도입함으로서 2차 소성 중에 의해 일어나는 ZnS의 상전이 및 EL 발광 휘도에 미치는 영향을 연구하였다. 즉 1차 소성된 형광체를 ball-mill 공정에서 인위적으로 표면에 defect를 형성시켜 ZnS의 저온상인 cubic으로의 전이가 용이하게 하여 EL구동하에서 발광 휘도를 증가시켰다. Ball-mill의 공정 변수로는 milling 시간과 rpm 등을 고려하여 각 조건에 따른 효과를 고찰하였으며, 발광 spectrum을 측정한 결과, 최적 조건에서 인위적인 결함을 형성하지 않은 형광체 보다 발광 휘도가 약 30% 이상 증가하였다. 또한 각기 다른 ball-mill 조건으로 합성된 형광체의 결정상을 분석하고 비교하였으며 상전이 특성에 따른 발광 휘도 변화를 고찰하였다.

• 한국추진공학회:학술대회논문집
• /
• 한국추진공학회 2006년도 제26회 춘계학술대회논문집
• /
• pp.209-212
• /
• 2006

본 논문에서는 항공기용 터보 축 엔진의 결함 진단 알고리즘을 개발하지 위해 Support Vector Machine(SVM)과 인공신경망(ANN)을 이용하였다. SVM을 이용하여 결함 위치를 판별한 후 인공신경망이 선택적으로 학습하는 분할 학습 알고리즘(SLA)을 제안하였으며 이를 고도 변화에 따른 가스 터빈 엔진의 결함 진단에 적용하여 분류 속도 및 예측 정확률 개선 가능성을 확인하였다.

• 한국추진공학회지
• /
• 제11권1호
• /
• pp.43-50
• /
• 2007

본 논문에서는 고도 변화만을 고려한 탈설계 영역에서 항공기용 터보 축 엔진의 결함 진단을 위해 지지 벡터 장치(SVM)과 인공신경망(ANN)을 Hybrid로 사용한 분할 학습 알고리즘을 사용하였다. 지상 정지 상태에서보다 학습 데이터와 테스트 데이터 수가 크게 증가하지만, 분할 학습 알고리즘을 이용한 가스터빈 엔진의 결함 진단이 고도 변화를 고려한 탈설계 영역에서도 높은 결함 예측 정확성을 가짐을 확인하였다.

• 한국추진공학회:학술대회논문집
• /
• 한국추진공학회 2008년도 제31회 추계학술대회논문집
• /
• pp.23-27
• /
• 2008

본 논문에서는 실수코드 유전 알고리즘(RCGA)과 인공신경망(ANN)을 이용하여 항공기용 터보 축엔진의 결함 진단에 관한 연구를 수행하였다. 인공신경망만을 이용하여 엔진의 결함을 판단 할 경우 많은 학습데이터 때문에 지역 최소점으로 수렴하는 단점이 있다. 이를 개선하기 위해 전역 최소점을 찾는 능력이 뛰어난 실수코드 유전 알고리즘을 사용하였다. 5% 이내의 RMS 결함오차로 높은 결함 예측 신뢰도를 가짐을 확인하였다.

• 반도체디스플레이기술학회지
• /
• 제22권2호
• /
• pp.40-44
• /
• 2023

The defect detection based on deep learning requires minimal loss and high accuracy to pinpoint product defects. In this paper, we confirm the loss rate of deep learning training based on disc-shaped artificial scaffold images. It is intended to compare the performance of Cross-Entropy functions used in object detection algorithms. The model was constructed using normal, defective artificial scaffold images and category cross entropy and sparse category cross entropy. The data was repeatedly learned five times using each loss function. The average loss rate, average accuracy, final loss rate, and final accuracy according to the loss function were confirmed.