• Journal of Korean Society of Industrial and Systems Engineering
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• v.25 no.6
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• pp.7-11
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• 2002

This paper estimates defect and outbreak probabilities of each individual component from some subset of masked data where the exact component causing system failure might be unknown. A system consists of k components that fails whenever there is a defect in at least one of the components. Due to cost and time constraints it is not feasible to learn exactly which components are defective. Because, test procedures ascertain that the defective components belong to some subset of the k components. This phenomenon is termed masking. We describe a, b, c type in which a sample of masked subsets is subjected to intensive failure analysis. This recorded data of a, b, c type enables maximum likelihood estimation of defect probability of each individual component and leads to outbreak of the defective components in future masked failures.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2005.07a
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• pp.149-150
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• 2005

Thyristor breakdown voltage variation acceleration aging test was investigated. The breakdown voltage was deceased after 1000 hours acceleration aging test. It temperature rising caused by electric field concentration at the edge beveling region of the thyristor was confirmed using Silvaco device simulation. The local temperature rising is driving force for the defect propagation. Consequently, propagated defects of the beveling region seems to decrease thyristor's breakdown voltage.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.4
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• pp.402-409
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• 2004

The purpose of this study is to investigate the effect of local wall thinning on the collapse of elbow subjected to internal pressure and bending moment. Thus, the nonlinear three-dimensional finite element analyses were performed to obtain the collapse moment of elbow containing various wall thinning defects located at intrados and extrados under two loading modes (closing and opening modes) with internal pressure. From the results of analysis, the effect of wall thinning defect on the global moment-rotation behavior of elbow was discussed, and the dependence of collapse moment of elbow on wall thinning depth, length, and circumferential angle was investigated under different loading mode and defect location.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.136-146
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• 2022

Some surface defects make the weak quality of steel materials. To limit these defects, we advocate a one-stage detector model RetinaNet among diverse detection algorithms in deep learning. There are several backbones in the RetinaNet model. We acknowledged two backbones, which are ResNet50 and VGG19. To validate our model, we compared and analyzed several traditional models, one-stage models like YOLO and SSD models and two-stage models like Faster-RCNN, EDDN, and Xception models, with simulations based on steel individual classes. We also performed the correlation of the time factor between one-stage and two-stage models. Comparative analysis shows that the proposed model achieves excellent results on the dataset of the Northeastern University surface defect detection dataset. We would like to work on different backbones to check the efficiency of the model for real world, increasing the datasets through augmentation and focus on improving our limitation.

• The Journal of Korean Academy of Prosthodontics
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• v.43 no.4
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• pp.487-497
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• 2005

Purpose: Resonance frequency analysis (RFA) , a non-invasive technique for the clinical measurement of implant stability, was investigated. Peri-implant bony defect may contribute to implant failure. This in vitro study evaluated the resonance frequencies according to various bony defects and determined whether the directional bone defect can affect the value of frequency analysis. Material and Method: Fifteen 3.75 mm in diameter and 10 mm in length, machined self-tapping implant future were used. Twelve types of bone defects that have different horizontal and vertical dimensions were simulated. Embedded implants were attached to the dental surveyor. Then, the transducer was connected with the implant fixture and the ISQ value was measured at four different directions. Two-way analysis of variance and post hoc $Sch\`{e}ffe'$ test were performed at the 95% significance level. Results: The control group showed the highest ISQ value and 5 thread-$360^{\circ}$ group had the lowest one. As the vertical exposure of implants in each angle was increased, the ISQ value was decreased. Although the horizontal exposure in each thread was increased, the ISQ value was not significantly decreased. Conclusion : Although the simulated defect type was different from each other, the ISQ value was similar among groups.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.11
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• pp.510-519
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• 2019

The aim of this study was to set a defect classification framework and evaluate the defect risks in apartment buildings For this, approximately 15,056 defect items for 133 apartment buildings were examined. As a result of the analysis, the major defect of the RC work was cracks, which were found mainly in public locations. Moreover, the RC work was found to exhibit a high defect risk of water problem and surface appearance, which are highly connected with cracks. Second, the finish work has a high defect risk because it is composed of various work types, and there are many kinds of materials and construction parts involved. Third, the major defects of the waterproof work were incorrect installation and missing tasks, which have high defect risks in the garage. This is because defects that require rework occur mainly in the underground garage. Based on these results, this study proposed countermeasures for defect risk management to be considered in the construction, handover, post-handover, and occupancy phases. These have been set in detail based on the three zones: low frequency high severity (LFHS), low frequency low severity (LFLS), and high frequency low severity (HFLS).

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.2 s.233
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• pp.253-261
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• 2005

In decades, a substantial body of work on a unified viscoplastic model which considers the mechanism of plastic deformation and creep deformation has developed. The systematic scheme for numerical analysis of unified model is necessary because the dominant failure mechanism is the defect growth and coalescence in materials. In the present study, the unified viscoplastic model for materials with defects suggested by Suquet and Michel was employed for numerical analysis. The constitutive equations are integrated based on the generalized mid-point rule and implemented into a finite element program (ABAQUS) by means of user-defined subroutine (UMAT). To evaluate the validity of the developed UMAT code and the assessment of the adopted viscoplastic model, the results obtained from the UMAT code was compared with the numerical reference solution and experimental data. The unit cell analysis also has been investigated to study the effect of strain rate, temperature, stress triaxiality and initial defect volume fraction on the growth and coalescence of the defect.

• Journal of Auto-vehicle Safety Association
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• v.7 no.4
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• pp.20-25
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• 2015

The basic point of a vehicle recall is to remove vehicle defects as soon as possible and thus prevent possible road traffic accidents caused by the defects beforehand. Therefore, the core of vehicle recall under the self-certification system consists of a timely response and fast remedy of defects. The present study aimed to deduce a plan for improvement of the system necessary for the fast remedy of defects through a phased analysis of defect investigation procedure based on defect investigation statistical data. There will be a need to make the TSB(Technical Service Bulletin) or service campaign data submission of a manufacturer compulsory for the collection of broad defect information in the stage of information analysis and to impose a higher penalty when the manufacturer violates the data submission in the investigation stage. In addition, it is considered that an active service campaign should be induced and a punishment for late recall will be needed for consumer protection.

• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1008-1010
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• 2005

In the examination of steam generator(SG) tube in nuclear power plant, eddy current testing probes play an important role in detecting the defects. Bobbin probe and MRPC probe is usually used for the inspection of SG tube. Bobbin probe is good at high speed inspection, but ability of detection of circumferential defect is very weak. On the contrary MRPC probe, which moves for inspection in the direction of axial and circumferential simultaneously, has very slow inspection speed, but it has excellent detection capability for small cracks, which is hardly detected by bobbin probe. In this paper, for the accurate analysis of experimental ECT signals, construction of MRPC probe signals database according to the variation of defect size is the main purpose. Using 3-D finite element method, ECT signals are analyzed, and signals analysis add according to frequency ingredient. The results, which are analysis and characteristics ion of electromagnetism simulation signals, is databased.

• Smart Structures and Systems
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• v.21 no.5
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• pp.687-694
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• 2018

The problem of wheel tread defects has become a major challenge for the health management of high-speed rail as a wheel defect with small radius deviation may suffice to give rise to severe damage on both the train bogie components and the track structure when a train runs at high speeds. It is thus highly desirable to detect the defects soon after their occurrences and then conduct wheel turning for the defective wheelsets. Online wheel condition monitoring using wheel impact load detector (WILD) can be an effective solution, since it can assess the wheel condition and detect potential defects during train passage. This study aims to develop an FBG-based track-side wheel condition monitoring method for the detection of wheel tread defects. The track-side sensing system uses two FBG strain gauge arrays mounted on the rail foot, measuring the dynamic strains of the paired rails excited by passing wheelsets. Each FBG array has a length of about 3 m, slightly longer than the wheel circumference to ensure a full coverage for the detection of any potential defect on the tread. A defect detection algorithm is developed for using the online-monitored rail responses to identify the potential wheel tread defects. This algorithm consists of three steps: 1) strain data pre-processing by using a data smoothing technique to remove the trends; 2) diagnosis of novel responses by outlier analysis for the normalized data; and 3) local defect identification by a refined analysis on the novel responses extracted in Step 2. To verify the proposed method, a field test was conducted using a test train incorporating defective wheels. The train ran at different speeds on an instrumented track with the purpose of wheel condition monitoring. By using the proposed method to process the monitoring data, all the defects were identified and the results agreed well with those from the static inspection of the wheelsets in the depot. A comparison is also drawn for the detection accuracy under different running speeds of the test train, and the results show that the proposed method can achieve a satisfactory accuracy in wheel defect detection when the train runs at a speed higher than 30 kph. Some minor defects with a depth of 0.05 mm~0.06 mm are also successfully detected.