• Nuclear Engineering and Technology
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• 제53권7호
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• pp.2357-2363
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• 2021

Silicon carbide is widely used in radiation environments due to its excellent properties. However, when exposed to the strong radiation environment constantly, plenty of defects are generated, thus causing the material performance downgrades or failures. In this paper, the two-temperature model (2T-MD) is used to explore the defect recovery process by applying the electronic energy loss (Se) on the pre-damaged system. The effects of defect concentration and the applied electronic energy loss on the defect recovery process are investigated, respectively. The results demonstrate that almost no defect recovery takes place until the defect density in the damage region or the local defect density is large enough, and the probability of defect recovery increases with the defect concentration. Additionally, the results indicate that the defect recovery induced by swift heavy ions is mainly connected with the homogeneous recombination of the carbon defects, while the probability of heterogeneous recombination is mainly dependent on the silicon defects.

• Journal of Information Processing Systems
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• 제19권6호
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• pp.745-755
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• 2023

The wire rope is an indispensable production machinery in coal mines. It is the main force-bearing equipment of the underground traction system. Accurate detection of wire rope defects and positions exerts an exceedingly crucial role in safe production. The existing defect detection solutions exhibit some deficiencies pertaining to the flexibility, accuracy and real-time performance of wire rope defect detection. To solve the aforementioned problems, this study utilizes the camera to sample the wire rope before the well entry, and proposes an object based on YOLOv5. The surface small-defect detection model realizes the accurate detection of small defects outside the wire rope. The transfer learning method is also introduced to enhance the model accuracy of small sample training. Herein, the enhanced YOLOv5 algorithm effectively enhances the accuracy of target detection and solves the defect detection problem of wire rope utilized in mine, and somewhat avoids accidents occasioned by wire rope damage. After a large number of experiments, it is revealed that in the task of wire rope defect detection, the average correctness rate and the average accuracy rate of the model are significantly enhanced with those before the modification, and that the detection speed can be maintained at a real-time level.

• 제어로봇시스템학회논문지
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• 제10권6호
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• pp.487-493
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• 2004

In this Paper, we propose a lighting system for the stable detection of check defects of the CRT panel through the analysis of the lighting interaction between the lighting unit and the CRT panel. The check defect is very difficult to detect reliably because of its high sensitivity according to the direction of incident light. At first, we model the physical shape of check defects using SEM image. And then we apply physics based illumination model to investigate the optical characteristics of the check defect. Finally, we propose a lighting system for the stable detection of check defect. Experimental results show the feasibility of the proposed lighting system for check inspection.

• Journal of Magnetics
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• 제21권3호
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• pp.437-441
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• 2016

Dipole model based analytical expression is proposed to estimate the length and depth of the rectangular defect on ferromagnetic pipe. Among the three leakage profiles of Magnetic Flux Leakage (MFL), radial and axial leakage profiles are considered in this work. Permeability variation of the specimen is ignored by considering the flux density as close to saturation level of the inspected specimen. Comparing the profile of both the components, radial leakage profile furnishes the better estimation of defect parameter. This is evident from the results of error percentage of length and depth of the defect. Normalized pattern of the proposed analytical model radial leakage profile is good agreement with the experimentally obtained profile support the performance of proposed expression.

• 대한기계학회논문집A
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• 제29권7호
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• pp.947-954
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• 2005

The purpose of this study is to develop failure pressure evaluation models, which are applicable to straight pipes and elbows containing an internally wall thinning defect induced by flow-accelerated-corrosion (FAC). In this study, thus, three dimensional finite element (FE) analyses are performed to investigate the dependences of failure pressure of internally wall thinned pipe on the defect shape, the pipe geometry, and the defect location and bend radius of elbow. Also, the existing failure pressure assessment models for externally wall thinned pipes are examined. Based on these, the new models for assessing failure pressure of piping components with an internally wall thinning defect are proposed. Comparison of failure pressure, predicted by proposed models, with FE analysis result shows good agreement regardless of pipe type, defect shape, and defect location and bend radius.

• 한국정보시스템학회지:정보시스템연구
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• 제32권4호
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• pp.149-162
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• 2023

Purpose In the textile industry, fabric defects significantly impact product quality and consumer satisfaction. This research seeks to enhance defect detection by developing a transformer-based deep learning image segmentation model for learning high-dimensional image features, overcoming the limitations of traditional image classification methods. Design/methodology/approach This study utilizes the ZJU-Leaper dataset to develop a model for detecting defects in fabrics. The ZJU-Leaper dataset includes defects such as presses, stains, warps, and scratches across various fabric patterns. The dataset was built using the defect labeling and image files from ZJU-Leaper, and experiments were conducted with deep learning image segmentation models including Deeplabv3, SegformerB0, SegformerB1, and Dinov2. Findings The experimental results of this study indicate that the SegformerB1 model achieved the highest performance with an mIOU of 83.61% and a Pixel F1 Score of 81.84%. The SegformerB1 model excelled in sensitivity for detecting fabric defect areas compared to other models. Detailed analysis of its inferences showed accurate predictions of diverse defects, such as stains and fine scratches, within intricated fabric designs.

• 제어로봇시스템학회논문지
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• 제14권5호
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• pp.415-419
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• 2008

Detecting and correcting defects on LCD glasses early in the manufacturing process becomes important for panel makers to reduce the manufacturing costs and to improve productivity. Many attempts have been made and were successfully applied to detect and identify simple defects such as scratches, dents, and foreign objects on glasses. However, it is still difficult to robustly detect low-contrast defect region, called Mura or blemish area on glasses. Typically, these defect areas are roughly defined as relatively large, several millimeters of diameter, and relatively dark and/or bright region of low Signal-to-Noise Ratio (SNR) against background of low-frequency signal. The aim of this article is to present a robust algorithm to segment these blemish defects. Early 90's, a highly robust estimator, known as the Model-Fitting (MF) estimator was developed by X. Zhuang et. al. and have been successfully used in many computer vision application. Compared to the conventional Least-Square (LS) estimator the MF estimator can successfully estimate model parameters from a dataset of contaminated Gaussian mixture. Such a noise model is defined as a regular white Gaussian noise model with probability $1-\varepsilon$ plus an outlier process with probability $varepsilon$. In the sense of robust estimation, the blemish defect in images can be considered as being a group of outliers in the process of estimating image background model parameters. The algorithm developed in this paper uses a modified MF estimator to robustly estimate the background model and as a by-product to segment the blemish defects, the outliers.

• 한국정보과학회논문지:소프트웨어및응용
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• 제33권7호
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• pp.605-614
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• 2006

성공적인 소프트웨어 개발은 QCD에 의해 결정되며, 그 중 Quality는 Cost와 Delivery를 결정하는 핵심요소이기도 하다. 그리고 소프트웨어의 규모와 복잡도가 증가함에 따라 quality의 조기 확보의 중요성이 점차 커지고 있다. 이러한 관점에서 개발 후 결함을 찾아내고 수정하는 것보다 결함예방을 위해 더 많은 노력을 기울여야 할 것이다. 결함 예방을 위해서는 peer review, testing과 같은 결함 식별활동과 함께 기존에 발생된 defect 에 대한 분석을 통해 발생 가능한 결함의 주업을 차단하는 활동이 필요하며, 이를 위해 기존의 품질 데이타의 조직화 및 활용이 필요하다. 소프트웨어의 품질 예방을 위한 방법으로 system safety 확보를 위해 사용되고 있는 FMEA를 활용할 수 있다. SW-FMEA(Software Fault Mode Effect Analysis)는 예측을 통해 결함을 예방하는 방법으로, 기존에는 요구사항 분석 및 설계 시 많이 활용되어 왔다 이러한 SW-FMEA는 개발 활동을 통해 측정되는 정보를 활용하여, 분석, 설계, 나아가 peer review나 testing 둥 개발 및 관리 활동에 적용하여 결함예방 (defect prevention) 의 수단으로 활용 할 수 있다. 본 논문에서는 기존에 시스템 분석, 설계에 focusing된 SW-FMEA를 변형하여 product 결합뿐 아니라, 개발과정 중 발생할 수 있는 fault를 줄일 수 있는 결함 예방 model을 제안한다.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2001년도 제4회 압출 및 인발가공 심포지엄
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• pp.1-12
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• 2001

In cold forging of piston-pin for automobile parts, the flow defect appears by the dead metal zone. This appearance evidently happens in products with a thin piercing thickness for the dimension accuracy and the decrease of material loss. The best method that can prevent flow defect is removing dead metal zone. The purpose of this study is to investigate the material flow behavior of forward-backward extruded piston-pin through the relative velocity ratio and the stroke control of upper moving punch & container using the flow control forming technique. The finite element simulations are applied to analyse the flow defect, then the results are compared with the plasticine model material experiments. Finally, the model experiment results are in good agreement with the FE simulation ones.

• 대한기계학회논문집A
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• 제26권7호
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• pp.1366-1375
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• 2002

In cold forging of piston-pin for automobile parts, the flow defect appears by the dead metal zone. This appearance evidently happens in products with a thin piercing thickness for the dimension accuracy and the decrease of material loss. The best method that can prevent flow defect is removing dead metal zone. The purpose of this study is to investigate the material flow behavior of forward-backward extruded piston-pin through the relative velocity ratio and the stroke control of upper moving punch & container using the flow control forming technique. The finite element simulations are applied to analyse the flow defect, then the results are compared with the plasticine model material experiments. The model experiment results are in good agreement with the FE simulation ones.