• Journal of the Semiconductor & Display Technology
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• v.22 no.4
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• pp.131-135
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• 2023

Neural network-based time series models called time series neural networks (TSNNs) are trained by the error backpropagation algorithm and used to predict process shifts of parameters such as gas flow, RF power, and chamber pressure in reactive ion etching (RIE). The training data consists of process conditions, as well as principal components (PCs) of optical emission spectroscopy (OES) data collected in-situ. Data are generated during the etching of benzocyclobutene (BCB) in a SF₆/O₂ plasma. Combinations of baseline and faulty responses for each process parameter are simulated, and a moving average of TSNN predictions successfully identifies process shifts in the recipe parameters for various degrees of faults.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.595-601
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• 2020

During the safety inspection of nitrocellulose-made explosive containers stored for more than 10 years, cracks were found in the containers. Therefore, a failure cause analysis test was performed. First, the cause of failure through the failure tree analysis was conducted to select the factors that influenced failure. The changes in the properties of the container caused by the acceleration of the reaction were found to be the cause of the failure by confirming the influence on the environment and internal/external factors that may occur during storage. To confirm this, environmental tests, such as thermal shock test and vacuum thermal stability test, were performed using a naturally aged container to analyze the cause of failure, and an accelerated aging test was performed to reproduce the failure. Through this, the chemical reaction was accelerated by heat and charge, as in the result of the fault tree analysis, and it was confirmed that the physical properties of the container were changed. In addition, the service life of the container was estimated using the Arrhenius model for the storage life due to thermal aging.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1445-1449
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• 2005

The ram assembly is important equipment in fueling machine of PHWR(Pressurized Heavy Water Reactor) plant where fuel replacement is possible while the plant is in service. Troubles in the ram assembly can cause lots of difficulties in power plant operation. The ram assembly is typically composed of the B-ram, the L-Ram and the C-Ram. The B-ram is focused in this paper because it plays the most important role in the ram assembly. Among the ram fault phenomena, ram stuck phenomena are the most frequent cases in the B-ram, which has a ball screw mechanism driven by a hydraulic motor. Ram stuck phenomena are due to ball wear and damage in ball nut that increase in proportion to the number of fuel replacement. It is required to predict ram stuck phenomena before they occur. In this paper, a method is proposed for predicting ram stuck phenomena using a discrete wavelet transform. The discrete wavelet transform provides information on both the time and frequency characteristics of the input signals. The proposed method uses the frequency bandwidths of coefficients of discrete wavelet decompositions and detail coefficients of discrete wavelet transform to predict ram stuck phenomena. The signal used in this paper is a torque-related signal such as a hydraulic service outlet pressure signal in a hydraulic driving system or a current signal in a DC motor driving system. Finally, the validity of the proposed method is shown via experiment using ball nut characteristic test equipment that simulates ram stuck phenomena due to increased ball friction in ball nut.

• Earthquakes and Structures
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• v.8 no.6
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• pp.1363-1386
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• 2015

The October 23 2011 Van Earthquake is studied from an earthquake engineering point of view. Strong ground motion processing was performed to investigate features of the earthquake source, forward directivity effects during the rupture process as well as local site effects. Strong motion characteristics were investigated in terms of peak ground motion and spectral acceleration values. Directiviy effects were discussed in detail via elastic response spectra and wide band spectograms to see the high frequency energy distributions. Source parameters and slip distribution results of the earthquake which had been proposed by different researchers were summarized. Influence of the source parameters on structural response were shown by comparing elastic response spectra of Muradiye synthetic records which were performed by broadband strong motion simulations of the earthquake. It has been emphasized that characteristics of the earthquake rupture dynamics and their effects on structural design might be investigated from a multidisciplinary point of view. Seismotectonic calculations (e.g., slip pattern, rupture velocity) may be extended relating different engineering parameters (e.g., interstorey drifts, spectral accelerations) across different disciplines while using code based seismic design approaches. Current state of the art building codes still far from fully reflecting earthquake source related parameters into design rules. Some of those deficiencies and recent efforts to overcome these problems were also mentioned. Next generation ground motion prediction equations (GMPEs) may be incorporated with certain site categories for site effects. Likewise in the 2011 Van Earthquake, Reverse/Oblique earthquakes indicate that GMPEs need to be feasible to a wider range of magnitudes and distances in engineering practice. Due to the reverse faulting with large slip and dip angles, vertical displacements along with directivity and fault normal effects might significantly affect the engineering structures. Main reason of excessive damage in the town of Erciş can be attributed to these factors. Such effects should be considered in advance through the establishment of vertical design spectra and effects might be incorporated in the available GMPEs.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2843-2845
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• 2000

A lane detection based on a road model or feature all need correct acquirement of information on the lane in a image, It is inefficient to implement a lane detection algorithm through the full range of a image when being applied to a real road in real time because of the calculating time. This paper defines two searching range of detecting lane in a road, First is searching mode that is searching the lane without any prior information of a road, Second is recognition mode, which is able to reduce the size and change the position of a searching range by predicting the position of a lane through the acquired information in a previous frame. It is allow to extract accurately and efficiently the edge candidates points of a lane as not conducting an unnecessary searching. By means of removing the perspective effect of the edge candidate points which are acquired by using the inverse perspective transformation, we transform the edge candidate information in the Image Coordinate System(ICS) into the plane-view image in the World Coordinate System(WCS). We define linear approximation filter and remove the fault edge candidate points by using it This paper aims to approximate more correctly the lane of an actual road by applying the least-mean square method with the fault-removed edge information for curve fitting.

• Journal of the Korean Society for Railway
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• v.10 no.5
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• pp.527-532
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• 2007

In this paper, we suggest those two design plans for power supply method of Hot Standby Sparing System; one is the plan using MTBF based on Constant Failure Rate, and the plan using Reliability Function is the other. Traditionally, RBD (Reliability Block Diagram) is used for reliability prediction which is required to meet any requirements before system operation. However, the system that has redundancy, such as Hot Standby Sparing System, Is not suitable for system reliability modeling using combination model, such as RBD. In this paper, therefore, we demonstrate that for redundancy controller, redundancy modeling design toward fault occurrence design is more effective to build up a system with higher reliability and achieve the effectiveness of loss cost due to maintenance and failure occurred in operation, rather than combinational modeling design.

• Journal of Convergence for Information Technology
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• v.9 no.8
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• pp.20-26
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• 2019

In this study, the optimal shape parameter condition is presented after analyzing the attributes of the software reliability model according to the change of the shape parameter of Loma life distribution with infinite fault NHPP. In order to analyze the software failure phenomena, the parametric estimation method was applied to the Maximum Likelihood Estimation method, and the nonlinear equation was applied to the bisection method. As a result, it was found that when the attributes according to the change of the shape parameter are compared, the smaller the shape parameter is, the better the prediction ability of the true value, and reliability attributes are efficient. Through this study, it is expected that software developers can increase reliability by preliminarily grasping the type of software failure based on shape parameter, and can be used as basic information to improve the software reliability attributes.

• Earthquakes and Structures
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• v.22 no.5
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• pp.503-515
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• 2022

This paper presents the development of seismic fragility curves for a precast reinforced concrete bridge instrumented with a structural health monitoring (SHM) system. The bridge is located near an active seismic fault in the Dominican Republic (DR) and provides the only access to several local communities in the aftermath of a potential damaging earthquake; moreover, the sample bridge was designed with outdated building codes and uses structural detailing not adequate for structures in seismic regions. The bridge was instrumented with an SHM system to extract information about its state of structural integrity and estimate its seismic performance. The data obtained from the SHM system is integrated with structural models to develop a set of fragility curves to be used as a quantitative measure of the expected damage; the fragility curves provide an estimate of the probability that the structure will exceed different damage limit states as a function of an earthquake intensity measure. To obtain the fragility curves a digital twin of the bridge is developed combining a computational finite element model and the information extracted from the SHM system. The digital twin is used as a response prediction tool that minimizes modeling uncertainty, significantly improving the predicting capability of the model and the accuracy of the fragility curves. The digital twin was used to perform a nonlinear incremental dynamic analysis (IDA) with selected ground motions that are consistent with the seismic fault and site characteristics. The fragility curves show that for the maximum expected acceleration (with a 2% probability of exceedance in 50 years) the structure has a 62% probability of undergoing extensive damage. This is the first study presenting fragility curves for civil infrastructure in the DR and the proposed methodology can be extended to other structures to support disaster mitigation and post-disaster decision-making strategies.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.36-42
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• 2021

With recent developments in the Fourth Industrial Revolution, the manufacturing industry has changed rapidly. Through key aspects of Fourth Industrial Revolution super-connections and super-intelligence, machine learning will be able to make fault predictions during the foam-making process. Polyol and isocyanate are components in polyurethane foam. There has been a lot of research that could affect the characteristics of the products, depending on the specific mixture ratio and temperature. Based on these characteristics, this study collects data from each factor during the foam-making process and applies them to machine learning in order to predict faults. The algorithms used in machine learning are the decision tree, kNN, and an ensemble algorithm, and these algorithms learn from 5,147 cases. Based on 1,000 pieces of data for validation, the learning results show up to 98.5% accuracy using the ensemble algorithm. Therefore, the results confirm the faults of currently produced parts by collecting real-time data from each factor during the foam-making process. Furthermore, control of each of the factors may improve the fault rate.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.6
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• pp.451-468
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• 2021

Predicting hazardous ground conditions ahead of a TBM (Tunnel Boring Machine) tunnel face is essential for efficient and stable TBM advance. Although there have been several studies on the electrical resistivity survey method for TBM tunnelling, sufficient experimental data considering TBM advance were not established yet. Therefore, in this study, the laboratory-scale model experiments for simulating TBM excavation were carried out to analyze the applicability of an electrical resistivity survey for predicting hazardous ground conditions ahead of a TBM tunnel face. The trend of electrical resistivity during TBM advance was experimentally evaluated under various hazardous ground conditions (fault zone, seawater intruded zone, soil to rock transition zone, and rock to soil transition zone) ahead of a tunnel face. In the course of the experiments, a scale-down rock ground was provided using granite blocks to simulate the rock TBM tunnelling. Based on the experimental data, the electrical resistivity tends to decrease as the tunnel approaches the fault zone. While the seawater intruded zone follows a similar trend with the fault zone, the resistivity value of the seawater intrude zone decreased significantly compared to that of the fault zone. In case of the soil-to-rock transition zone, the electrical resistivity increases as the TBM approaches the rock with relatively high electrical resistivity. Conversely, in case of the rock-to-soil transition zone, the opposite trend was observed. That is, electrical resistivity decreases as the tunnel face approaches the rock with relatively low electrical resistivity. The experiment results represent that hazardous ground conditions (fault zone, seawater intruded zone, soil-to-rock transition zone, rock-to-soil transition zone) can be efficiently predicted by utilizing an electrical resistivity survey during TBM tunnelling.