• Journal of the Earthquake Engineering Society of Korea
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• v.11 no.4
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• pp.25-31
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• 2007

For areas such as the Korean Peninsula, which have moderate seismic activity but no available records of strong ground motion, synthetic seismograms can be used to evaluate ground motion without waiting for a strong earthquake. Such seismograms represent the estimated ground motions expected from a set of possible earthquake scenarios. Local site effects are especially important in assessing the seismic hazard and possible ground motion scenarios for a specific fault. The earthquake source and rupture dynamics can be described as a two-step process of rupture initiation and front propagation controlled by a frictional sliding mechanism. The seismic wavefield propagates through heterogeneous geological media and finally undergoes near-surface modulations such as amplification or deamplification. This is a complex system in which various scales of physical phenomena are integrated. A unified approach incorporates multi-scale problems of dynamic rupture, radiated wave propagation, and site effects into an all-in-one model using a three-dimensional, fourth-order, staggered-grid, finite-difference method. The method explains strong ground motions as products of complex systems that can be modified according to a variety of fine-scale rupture scenarios and friction models. A series of such deterministic earthquake scenarios can shed light on the kind of damage that would result and where it would be located.

• International Journal of Quality Innovation
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• v.6 no.1
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• pp.109-118
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• 2005

The parameter design is the most emphasized measure by researchers for a new products development. It is critical for makers to achieve simultaneously in both the time-to-market production and the quality enhancement. However, there are difficulties in practical application, such as (1) complexity and nonlinear relationships co-existed among the system's inputs, outputs and control parameters, (2) interactions occurred among parameters, (3) where the adjustment factors of Taguchi's two-phase optimization procedure cannot be sure to exist in practice, and (4) for some reasons, the data became lost or were never available. For these incomplete data, the Taguchi methods cannot treat them well. Neural networks have a learning capability of fault tolerance and model free characteristics. These characteristics support the neural networks as a competitive tool in processing multivariable input-output implementation. The successful fields include diagnostics, robotics, scheduling, decision-making, prediction, etc. This research is a case study of spherical annealing model. In the beginning, an original model is used to pre-fix a model of parameter design. Then neural networks are introduced to achieve another model. Study results showed both of them could perform the highest spherical level of quality.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.983-989
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• 2015

Power transformer is one of the major and key apparatus in electric power system. Monitoring and diagnosis of transformer fault is necessary for improving the life period of transformer. The failures caused by short circuits are one of the causes of transformer outages. The short circuit currents induce excessive forces in the transformer windings which result in winding deformation affecting the mechanical and electrical characteristics of the winding. In the present work, a transformer producing only the radial flux under short circuit is considered. The corresponding axial displacement profile of the windings is computed using Finite Element Method based transient structural analysis and thus obtained displacements are compared with the experimental result. The change in inter disc capacitance and mutual inductance of the deformed windings due to different short circuit currents are computed using Finite Element Method based field analyses and the corresponding Sweep Frequency Responses are computed using the modified electrical equivalent circuit. From the change in the first resonant frequency, the winding movement can be quantified which will be useful for estimating the mechanical withstand capability of the winding for different short circuit currents in the design stage itself.

• Geomechanics and Engineering
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• v.18 no.2
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• pp.215-224
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• 2019

Excavation of long tunnels by shielded TBMs is a safe, fast, and efficient method of tunneling that mitigates many risks related to ground conditions. However, long-distance tunneling in great depth through adverse geological conditions brings about limitations in the application of TBMs. Among various harsh geological conditions, squeezing ground as a consequence of tunnel wall and face convergence could lead to cluttered blocking, shield jamming and in some cases failure in the support system. These issues or a combination of them could seriously hinder the performance of TBMs. The technique of excavation has a strong influence on the tunnel response when it is excavated under squeezing conditions. The Golab water conveyance tunnel was excavated by a double-shield TBM. This tunnel passes mainly through metamorphic weak rocks with up to 650 m overburden. These metamorphic rocks (Shales, Slates, Phyllites and Schists) together with some fault zones are incapable of sustaining high tangential stresses. Prediction of the convergence, estimation of the creeping effects and presenting strategies to overcome the squeezing ground are regarded as challenging tasks for the tunneling engineer. In this paper, the squeezing potential of the rock mass is investigated in specific regions by dint of numerical and analytical methods. Subsequently, several operational solutions which were conducted to counteract the challenges are explained in detail.

• Journal of Korean Society for Quality Management
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• v.47 no.1
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• pp.75-86
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• 2019

Purpose: It is essential for the steel industry to produce steel products without unexpected downtime to reduce costs and produce high quality products. A hot strip rolling mill consists of many mechanical and electrical units. In condition monitoring and diagnosis, various units could fail for unknown reasons. Methods: In this study, we propose an effective method to detect units with abnormal status early to minimize system downtime. The early warning problem with various units was first defined. An autoencoder was modeled to detect abnormal states. An application of the proposed method was also implemented in a simulated field-data analysis. Results: We can compare images of original data and reconstructed images, as well as visually identify differences between original and reconstruction images. We confirmed that normal and abnormal states can be distinguished by reconstruction error of autoencoder. Experimental results show the possibility of prediction due to the increase of reconstruction error from just before equipment failure. Conclusion: In this paper, hot strip roughing mill monitoring method using autoencoder is proposed and experiments are performed to study the benefit of the autoencoder.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.2
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• pp.14-22
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• 2021

A plan for the development of reliability-based ROK amphibious assault vehicles is proposed. By analyzing the development case of the U.S. EFV, considerations for the successful development of the next-generation Korea Forces amphibious assault vehicle are presented. If the vehicle reliability can be improved to the level of the fourth highest priority electric unit for power units, suspensions, decelerators, and body groups, which have the highest priority among fault frequency items, a system level MTBF of 36.4%↑ can be achieved, and the operational availability can be increased by 3.5%↑. The next-generation amphibious assault vehicles must fulfill certain operating and performance requirements, the underlying systems must be built, and sequencing of the hybrid engine and the modular concept should be considered. Along with big-data- and machine-learning-based failure prediction, machine maintenance based on augmented reality/virtual reality and remote maintenance should be used to improve the ability to maintain combat readiness and reduce lifecycle costs.

• Journal of Information Technology Services
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• v.20 no.3
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• pp.1-12
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• 2021

Reactor Coolant Pump (RCP) is core part of nuclear power plant to provide the forced circulation of reactor coolant for the removal of core heat. Properly monitoring vibration of RCP is a key activity of a successful predictive maintenance and can lead to a decrease in failure, optimization of machine performance, and a reduction of repair and maintenance costs. Here, we developed real-time RCP Vibration Analysis System (VAS) that web based platform using NoSQL DB (Mongo DB) to handle vibration data of RCP. In this paper, we explain how to implement digital signal process of vibration data from time domain to frequency domain using Fast Fourier transform and how to design NoSQL DB structure, how to implement web service using Java spring framework, JavaScript, High-Chart. We have implement various plot according to standard of the American Society of Mechanical Engineers (ASME) and it can show on web browser based on HTML 5. This data analysis platform shows a upgraded method to real-time analyze vibration data and easily uses without specialist. Furthermore to get better precision we have plan apply to additional machine learning technology.

• Journal of the Korean Society of Safety
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• v.38 no.5
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• pp.43-50
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• 2023

With the advent of industrialization, consumers and end-users demand more reliable products. Meeting these demands requires a comprehensive approach, involving tasks such as market information collection, planning, reliable raw material procurement, accurate reliability design, and prediction, including various reliability tests. Moreover, this encompasses aspects like reliability management during manufacturing, operational maintenance, and systematic failure information collection, interpretation, and feedback. Improving product reliability requires prioritizing it from the initial development stage. Failure mode and effect analysis (FMEA) is a widely used method to increase product reliability. In this study, we reanalyzed using the FMEA method and proposed an improved method. Domestic railways lack an accurate measurement method or system for maintenance, so maintenance decisions rely on the opinions of experienced personnel, based on their experience with past faults. However, the current selection method is flawed as it relies on human experience and memory capacity, which are limited and ineffective. Therefore, in this study, we further specify qualitative contents to systematically accumulate failure modes based on the Failure Modes Table and create a standardized form based on the Master FMEA form to newly systematize it.

• Fire Science and Engineering
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• v.31 no.1
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• pp.58-62
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• 2017

There is a growing need for seismic resistance design. But it is controversial that standards of sway brace device in non-structural elements for buildings like pump waterway is vary widely. Therefore, in this study to get a valid range of sway brace device in seismic resistance design, using load test of sway brace device. As a result, load of safe range from 0 to 18.5 kN and under 29.4 kN, no structural fault of sway brace device. And using internet of things get a data of seismic resistance design from sensor node like accelerometer, GPS, tilt sensor and temperature sensor through steps of sampling and prediction. These results will be acceptable for monitoring system for seismic resistance in non-structural elements.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.403-409
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• 2024

In this paper, the guidelines for the design of an Artificial Intelligence(AI) based Integrated Process Safety Management(PSM) system to enhance workplace safety using data from process safety reports submitted by hazardous and risky facility operators in accordance with the Occupational Safety and Health Act is proposed. The system composed of the proposed guidelines is to be implemented separately by individual facility operators and specialized process safety management agencies for single or multiple workplaces. It is structured with key components and stages, including data collection and preprocessing, expansion and segmentation, labeling, and the construction of training datasets. It enables the collection of process operation data and change approval data from various processes, allowing potential fault prediction and maintenance planning through the analysis of all data generated in workplace operations, thereby supporting decision-making during process operation. Moreover, it offers utility and effectiveness in time and cost savings, detection and prediction of various risk factors, including human errors, and continuous model improvement through the use of accurate and reliable training data and specialized datasets. Through this approach, it becomes possible to enhance workplace safety and prevent accidents.