• Journal of Platform Technology
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• v.6 no.2
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• pp.19-25
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• 2018

Existing Photovoltaic(PV) monitoring system monitors the current, past power generation, all values of environmental sensors. It is necessary to predict solar power generation for efficient operation and maintenance on the power plant. We propose a method for estimating the generation of PV data based PV monitoring system with data accumulation. Through this, we intend to find the failure prediction of the photovoltaic power plant in proportion to the predicted power generation. As a result, the administrator can predict the failure of the system it will be prepared in advance.

• Advances in concrete construction
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• v.11 no.2
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• pp.111-126
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• 2021

Concrete cracking due to brittle tension strength significantly prevents fully utilization of the materials for "flexural-shear failure" type shear walls. Theoretical and experimental studies applying fiber reinforced concrete (FRC) have achieved fruitful results in improving the seismic performance of "flexural-shear failure" reinforced concrete shear walls. To come to an understanding of an optimal design strategy and find common performance prediction method for design methodology in terms to FRC shear walls, seismic performance on shear walls with PVA and steel FRC at edge columns and plastic region are compared in this study. The seismic behavior including damage mode, lateral bearing capacity, deformation capacity, and energy dissipation capacity are analyzed on different fiber reinforcing strategies. The experimental comparison realized that the lateral strength and deformation capacity are significantly improved for the shear walls with PVA and steel FRC in the plastic region and PVA FRC in the edge columns; PVA FRC improves both in tensile crack prevention and shear tolerance while steel FRC shows enhancement mainly in shear resistance. Moreover, the tensile strength of the FRC are suggested to be considered, and the steel bars in the tension edge reaches the ultimate strength for the confinement of the FRC in the yield and maximum lateral bearing capacity prediction comparing with the model specified in provisions.

• Nuclear Engineering and Technology
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• v.56 no.1
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• pp.48-55
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• 2024

The safety-related raw water system's strong operational condition supports the radiation defense and biological shield of nuclear plant containment structures. Gaps and failures in maintaining proper working condition of main equipment like pump were among the most common causes of unavailability of safety related raw water systems. We integrated the advanced data analytics tools to evaluate the maintenance records of water systems and gave special consideration to deficiencies related to pump. We utilized maintenance data over a three-and-a-half-year period to produce metrics like MTBF, MTTF, MTTR, and failure rate. The visual analytic platform using tableau identified the efficacy of maintenance & deficiency in the safety raw water systems. When the number of water quality violation was compared to the other O&M deficiencies, it was discovered that water quality violations account for roughly 15% of the system's deficiencies. The pumps were substantial contributors to the deficit. Pump availability was predicted and optimized with real time data using response surface method. The prediction model was significant with r-squared value of 0.98. This prediction model can be used to predict forth coming pump failures in nuclear plant.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.6
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• pp.1-10
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• 2023

The nuclear power plant(NPP)'s Instrumentation and Control(I&C) system periodically conducts integrity checks for the maintenance of self-diagnostic function during normal operation. Additionally, it performs functionality and performance checks during planned preventive maintenance periods. However, there is a need for technological development to diagnose failures and prevent accidents in advance. In this paper, we studied methods for estimating the reliability function by utilizing environmental data and self-diagnostic data of the I&C equipment. To obtain failure data, we assumed probability distributions for component features of the I&C equipment and generated virtual failure data. Using this failure data, we estimated the reliability function using representative artificial intelligence(AI) models used in survival analysis(DeepSurve, DeepHit). And we also estimated the reliability function through the Cox regression model of the traditional semi-parametric method. We confirmed the feasibility through the residual lifetime calculations based on environmental and diagnostic data.

• Korean Circulation Journal
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• v.53 no.9
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• pp.621-631
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• 2023

Background and Objectives: The morphology-voltage-P-wave duration (MVP) electrocardiography (ECG) risk score is a newly defined scoring system that has recently been used for atrial fibrillation (AF) prediction. The aim of this study was to evaluate the ability of the MVP ECG risk score to predict AF in patients with an implantable cardioverter defibrillator (ICD) and heart failure with reduced ejection fraction in long-term follow-up. Methods: The study used a single-center, and retrospective design. The study included 328 patients who underwent ICD implantation in our hospital between January 2010 and April 2021, diagnosed with heart failure. The patients were divided into low, intermediate and high-risk categories according to the MVP ECG risk scores. The long-term development of atrial fibrillation was compared among these 3 groups. Results: The low-risk group included 191 patients, the intermediate-risk group 114 patients, and the high-risk group 23 patients. The long-term AF development rate was 12.0% in the low-risk group, 21.9% in the intermediate risk group, and 78.3% in the high-risk group. Patients in the high-risk group were found to have 5.2 times higher rates of long-term AF occurrence compared to low-risk group. Conclusions: The MVP ECG risk score, which is an inexpensive, simple and easily accessible tool, was found to be a significant predictor of the development of AF in the long-term follow-up of patients with an ICD with heart failure with reduced ejection fraction. This risk score may be used to identify patients who require close follow-up for development and management of AF.

• 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.

• Proceedings of the Korean Society for Rock Mechanics Conference
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• 2008.10a
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• pp.183-190
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• 2008

• Proceedings of the Korea Water Resources Association Conference
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• 2005.09a
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• pp.733-734
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• 2005

• Korean Business Review
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• v.3
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• pp.123-153
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• 1990

• Proceedings of the Materials Research Society of Korea Conference
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• 2001.11a
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• pp.108-108
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• 2001