• Computational Structural Engineering
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• v.10 no.1
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• pp.173-183
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• 1997

In this paper a method is suggested for the probabilistic analysis of impact buckling failure time of cylinder with random axisymmetric geometric imperfection under axial impact. Failure is assumed as axisymmetric radial deformation exceeds the given criteria for the first time. For the generation of random geometric initial imperfection, random field theory by mean function and autocorrelation function of geometric imperfection is used. Suggested method is useful for the treatment of the randomness of realistic geometric imperfection and can be used for the structural safety analysis of cylinder considering its effect.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.5
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• pp.615-621
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• 2009

TFT-LCD image consists of ununiform background, random noises and target defect signal components. Defects in TFT-LCD have some intensity variations compared to background region. It is sometimes difficult for human inspectors to figure out. In this paper, we propose multi-level threshold scheme for detection of the real defect using probability density function with Parzen Window. The experimental results show that the proposed algorithms produce promising results and can be applied to automated inspection systems for finding defects in the TFT-LCD image.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1443-1444
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• 2007

지속적으로 증가되는 전기에너지 공급의 신뢰성을 높이기 위하여 전력설비 주요 사고 원인인 부분방전(PD : Partial Discharge)을 검출하고 결함원의 패턴인식 방법의 개발 필요성 날로 증가되고 있다. 본 논문은 부분방전의 패턴인식 확률을 높이기 위하여 검출된 부분방전의 주파수 분석을 이용하여 Conventional PRPD Analysis 방법의 결함 판독확률을 향상시키기 위하여 Advanced PRPD를 제안 한다. 이를 위하여, GIS(Gas Insulated Switchgear)의 주요 사고원인으로 인식되어 있는 결함들을 인위적으로 제작 후 삽입하여 부분방전을 발생시켜 자체 설계 개발된 UHF 내장형 센서를 이용하여 검출하였다. 새로이 제안하는 방법과 기존의 PRPD 방법의 인식률을 상호 비교하기 위하여, 두 가지 그룹을, 즉, 기존의 방법에 의한 것과 부분방전의 주파수 분석이 포함된 방법에 의한 데이터그룹을 구축하고 학습방법은 동일한 인공신경망 MLP (Multilayer Perceptron)를 이용하여 인식률과 학습시간을 동시에 비교하였다. 상호 비교 결과에 의하면, 후자의 방법이 인식확률 뿐만아니라 학습시간도 좋은 결과가 나타났다.

• Proceedings of the KSME Conference
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• 2001.11a
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• pp.155-160
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• 2001

This paper describes a probabilistic fracture mechanics (PFM) analysis based on Monte Carlo (MC) simulation. In the analysis of CANDU pressure tube, it is necessary to perform the PFM analyses based on statistical consideration of flaw generation time. A depth and an aspect ratio of initial semi-elliptical surface crack, a fracture toughness value, delayed hydride cracking (DHC) velocity, and flaw generation time are assumed to be probabilistic variables. In all the analyses, degradation of fracture toughness due to neutron irradiation is considered. Also, the failure criteria considered are plastic collapse, unstable fracture and crack penetration. For the crack growth by DHC, the failure probability was evaluated in due consideration of flaw generation time.

• Journal of the Korean Society for Nondestructive Testing
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• v.5 no.2
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• pp.53-57
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• 1986

이상적인 검사는 합부판정 기준보다 큰 결함을 100%검출, 불합격시키고 그보다 작은 결함은 100% 합격시킬 수 있으나 현실적으로 이는 불가능하고 검사의 본질적인 불확실성으로 인해 때로는 합격되어야 할 결함이 불합격으로 처리되거나 (TYPE 1 ERROR라 칭함) 불합격되어야 할 결함이 합격으로 처리되기도 한다. (TYPE 2 ERROR) TYPE 1 ERROR 및 TYPE 2 ERROR를 동시에 줄이기 위해서는 검사의 불확실성을 제거하여야 하며 주어진 합부판정 기준과 검사불확실성하에서 검사를 둘러싼 총경비를 최소화시키기 위하여는 TYPE 1 ERROR와 TYPE 2 ERROR의 확률 및 그로 인한 예상 경비를 관련시켜야 한다.

• Composites Research
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• v.37 no.3
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• pp.179-185
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• 2024

This study quantitatively evaluated and investigated the changes in transverse tensile strength of unidirectional fiber-reinforced composites with initial void defects using a Representative Volume Element (RVE) model. After calculating the appropriate sample size based on margin of error and confidence level for initial void defects, a sample group of 5000 RVE models with initial void defects was generated. Dimensional reduction and density-based clustering analysis were conducted on the sample group to assess similarity, confirming and verifying that the sample group was unbiased. The validated sample analysis results were represented using a Weibull distribution, allowing them to be applied to the reliability analysis of composite structures.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.6
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• pp.651-656
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• 2014

Corrosion has a significant influence upon the reliability assessment and the maintenance planning of gas pipeline. Corrosion defects occurred on the underground pipeline can be obtained by conducting periodic in-line inspection (ILI). However, little study has been done for practical use of ILI data. This paper deals with remaining lifetime prediction of the gas pipeline in the presence of corrosion defects. Because a pipeline parameter includes uncertainty in its operation, a probabilistic approach is adopted in this paper. A pipeline fails when its operating pressure is larger than the pipe failure pressure. In order to estimate the failure probability, this paper uses First Order Reliability Method (FORM) which is popular in the field of structural engineering. A well-known Battelle code is chosen as the computational model for the pipe failure pressure. This paper develops a Matlab GUI for illustrating failure probability predictions Our result indicates that clustering of corrosion defects is helpful for improving a prediction accuracy and preventing an unnecessary maintenance.

• Fire Science and Engineering
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• v.26 no.4
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• pp.31-41
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• 2012

This study collected 5,100 cases of gas accident occurred in Korea for 14 years from 1995 to 2008, established Database and based on it, analyzed them by detailed forms and reasons. As the result of analyzing the whole city gas accidents with Poisson analysis, the item of "Careless work-Explosion-Pipeline' showed the highest rate of accidents for the next 5 years. And, "Joint Losening and corrosion-Release-Pipeline" showed the lowest rate of accident. In addition, for the result of analyzing only accidents related to LPG vaporizer, "LPG-Vaporizer-Fire" showed the highest rate of accident and "LPG-Vaporizer-Products Faults" showed the lowest rate of accident. Also, as the result of comparing and analyzing foreign LPG accident accompanied by Jet fire, facility's defect which is liquid outflow cut-off device and heat exchanger's defect were analyzed as the main reason causing jet fire, like the case of Korea, but the number of accidents for the next 5 years was the highest in "LPG-Mechanical-Jet fire" and "LPG-Mechanical-Vapor Cloud" showed the highest rate of accidents. By grafting Poisson distribution theory onto gas accident expecting program of the future, it's expected to suggest consistent standard and be used as the scale which can be used in actual field.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.4
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• pp.577-586
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• 2022

Detection and classification of steel surface defects are critical for product quality control in the steel industry. However, due to its low accuracy and slow speed, the traditional approach cannot be effectively used in a production line. The current, widely used algorithm (based on deep learning) has an accuracy problem, and there are still rooms for development. This paper proposes a method of steel surface defect detection combining EfficientNetV2 for image classification and YOLOv5 as an object detector. Shorter training time and high accuracy are advantages of this model. Firstly, the image input into EfficientNetV2 model classifies defect classes and predicts probability of having defects. If the probability of having a defect is less than 0.25, the algorithm directly recognizes that the sample has no defects. Otherwise, the samples are further input into YOLOv5 to accomplish the defect detection process on the metal surface. Experiments show that proposed model has good performance on the NEU dataset with an accuracy of 98.3%. Simultaneously, the average training speed is shorter than other models.

• Annual Conference of KIPS
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• 2005.05a
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• pp.345-348
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• 2005

소프트웨어 결함은 그것을 찾아내는 것도 힘들지만 정확한 해법을 찾는 것도 쉽지 않을 뿐더러, 또 테스트자의 능력 여하에 따라 수정중에 새로운 결함이 도입될 수도 있기 때문에 검출된 결함이 완벽하게 제거되기는 쉽지 않다. 따라서, 결함 제거 효율은 개발중인 소프트웨어의 신뢰도 성장이나 테스트 및 수정비용에 영향을 크게 미친다. 이는 소프트웨어 개발의 모든 과정에서 매우 유용한 척도로서 개발자가 디버깅 효율을 평가하는데 크게 도움이 될 뿐더러, 추가로 소요되는 작업량을 예측할 수 있게 해준다. 그러므로 개발 소프트웨어의 신뢰도와 비용면에서 불완전 디버깅의 영향을 연구하는 것은 매우 중요하다고 할 수 있으며, 이는 최적 인도 시각이나 운영 예산에도 영향을 줄 수 있다. 본 논문에서는 개발중인 소프트웨어를 대상으로 하여 디버깅이 완전하지 않으며, 이 때문에 디버깅 중 새로운 결함이 도입될 수도 있다는 제안하에 보편적으로 사용되는 신뢰도 모델을 대상으로 불완전 디버깅 범위로까지 소프트웨어의 신뢰도와 비용 문제를 확장하여 연구한다.