• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.742-743
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• 2007

A maintenance plan of power system equipment reduces failure rate caused by equipment's age. To prevent unexpected failure, the maintenance is performed periodically according to the interval time. The more expansive equipment's scale is, the more the maintenance without considering costs sustains a economical loss. Hence, the maintenance's time and the cost must be considered when maintenance which is considering the reliability is implemented. In this paper, optimum maintenance interval is calculated by considering minimum maintenance cost of the equipment with the combined cycle units in Korea power systems.

• Steel and Composite Structures
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• v.21 no.5
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• pp.1145-1156
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• 2016

To study the effects of foam core density and face-sheet thickness on the mechanical properties and failure modes of aluminum foam sandwich (AFS) beam, especially when the aluminum foam core is made in aluminum alloy and the face sheet thickness is less than 1.5 mm, three-point bending tests were investigated experimentally by using WDW-50E electronic universal tensile testing machine. Load-displacement curves were recorded to understand the mechanical response and photographs were taken to capture the deformation process of the composite structures. Results demonstrated that when foam core was combined with face-sheet thickness of 0.8 mm, its carrying capacity improved with the increase of core density. But when the thickness of face-sheet increased from 0.8 mm to 1.2 mm, result was opposite. For AFS with the same core density, their carrying capacity increased with the face-sheet thickness, but failure modes of thin face-sheet AFS were completely different from the thick face-sheet AFS. There were three failure modes in the present research: yield damage of both core and bottom face-sheet (Failure mode I), yield damage of foam core (Failure mode II), debonding between the adhesive interface (Failure mode III).

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.8
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• pp.1177-1183
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• 2013

In this paper, the analysis of inspection period bases on reliability is suggested in the field of traction power system. Even though there are several maintenance models, the most commonly used maintenance assessment has been focused on time based maintenance in real traction power systems. The maintenance intervals are selected on the basis of long-time experience. It ensures high availability and exact planning of staff. Reliability centered maintenance, which evaluates criticality and severity of each failure mode, achieves the operation, maintenance, and cost-effective improvement that will manage the risks of equipment. This paper deals with electrification in railway inspection frequency and applied reliability based inspection frequency instead of constant intervals. The distribution function of failure rate in traction power system belongs to Weibull function. Also, the fault data and the number of installed equipments for electrifications are collected. The failure history is investigated and classified in detail. Though these complicated procedures, it contribute to extend equipment lifetime and to reduce maintenance costs.

• Proceedings of the Korean Geotechical Society Conference
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• 2002.10a
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• pp.279-286
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• 2002

Present all sorts of failure or no failure test methods are done for evaluate structural ability of pavement. It are Plane Plate Test, CBR Test, Benkelman Beam Test, FWD, Dynaflect, etc. but, each method of test not expect compatibility because the result very different by each method of test. Now among pavement's method of evaluation, no failure test gradually use because It quickly and simply obtain pavement's elastic modulus of each layer. But, It accompany expensiveness equipment, and It's degree of trust is lower against expensiveness equipment. Therefore this research practice comparative trustworthy Plane Plate Test, comparative low cost and quick Small FWD Test. And analyzed relation of Plane Plate Test with Small FWD Test.

• Journal of the Korea Institute of Military Science and Technology
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• v.9 no.2 s.25
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• pp.51-59
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• 2006

The purpose of this paper is to present reliability analysis procedures for repairable systems and apply the procedures for assessing the reliabilities of two subsystems of a specific group of military equipment based on field failure data. The mean cumulative function, M(t), the average repair rate, ARR(t), and analytic test methods are used to determine whether a failure process follows a renewal or non-renewal process. For subsystem A, the failure process turns out to follow a homogeneous Poisson process, and subsequently, its mean time between failures, availability, and the necessary number of spares are estimated. For subsystem B, the corresponding M(t) plot shows an increasing trend, indicating that its failure process follows a non-renewal process. Therefore, its M(t) is modeled as a power function of t, and a preventive maintenance policy is proposed based on the annual mean repair cost.

• International Journal of Railway
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• v.3 no.1
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• pp.34-37
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• 2010

In recent, the railway system consists of subsystems as rolling stock and infrastructures as signaling, telecommunication, power supply, overhead contact and platform screen door, etc. Furthermore, each subsystem has complicated interface so as not to understand these relationship. Consequently, to operate the railway system continuously with required safety and availability, the failure data should be corrected and analyzed systematically during operation. To achieve this object effectively, this paper presents the method which is evaluating the operational risk quantitatively using failure data, and selecting the critical equipment. Following this analysis, the improvement plan is established and applied to reduce the operational risk on system or equipment. From this study, the critical equipments of system could be determined and prioritized by risk analysis. Also, the effective maintenance to prevent critical failure could be implanted by this suggested methodology.

• Communications for Statistical Applications and Methods
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• v.29 no.2
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• pp.151-160
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• 2022

The total system is composed of the main system (MS) and the failure detection equipment (FDE) which detects failures of MS. The analysis of system reliability is performed when the failure of FDE is possible. Several repair policies are considered to determine the order of repair of failed systems, which are sequential repair (SQ), priority repair (PR), independent repair (ID), and simultaneous repair (SM). The states of MS-FDE systems are represented by Markov models according to repair policies and the main purpose of this paper is to derive the system availabilities of the Markov models. Analytical solutions of the stationary equations are derived for the Markov models and the system availabilities are immediately determined using the stationary solutions. A simple illustrative example is discussed for the comparison of availability values of the repair policies considered in this paper.

• Journal of Korean Society for Quality Management
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• v.49 no.4
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• pp.581-594
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• 2021

Purpose: The purpose of this study is to compare machine learning models for anomaly detection of mechanical facility equipment and suggest an anomaly detection system for mechanical facility equipment in subway stations. It helps to predict failures and plan the maintenance of facility. Ultimately it aims to improve the quality of facility equipment. Methods: The data collected from Daejeon Metropolitan Rapid Transit Corporation was used in this experiment. The experiment was performed using Python, Scikit-learn, tensorflow 2.0 for preprocessing and machine learning. Also it was conducted in two failure states of the equipment. We compared and analyzed five unsupervised machine learning models focused on model Long Short-Term Memory Variational Autoencoder(LSTM-VAE). Results: In both experiments, change in vibration and current data was observed when there is a defect. When the rotating body failure was happened, the magnitude of vibration has increased but current has decreased. In situation of axis alignment failure, both of vibration and current have increased. In addition, model LSTM-VAE showed superior accuracy than the other four base-line models. Conclusion: According to the results, model LSTM-VAE showed outstanding performance with more than 97% of accuracy in the experiments. Thus, the quality of mechanical facility equipment will be improved if the proposed anomaly detection system is established with this model used.

• Journal of Power Electronics
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• v.16 no.4
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• pp.1426-1437
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• 2016

In different industrial and mission oriented applications, redundant or standby semiconductor systems can be implemented to improve the reliability of power electronics equipment. The proper structure for implementation can be one of the redundant or standby structures for series or parallel switches. This selection is determined according to the type and failure rate of the fault. In this paper, the reliability and the mean time to failure (MTTF) for each of the series and parallel configurations in two redundant and standby structures of semiconductor switches have been studied based on different failure rates. The Markov model is used for reliability and MTTF equation acquisitions. According to the different values for the reliability of the series and parallel structures during SC and OC faults, a comprehensive comparison between each of the series and parallel structures for different failure rates will be made. According to the type of fault and the structure of the switches, the reliability of the switches in the redundant structure is higher than that in the other structures. Furthermore, the performance of the proposed series and parallel structures of switches during SC and OC faults, results in an improvement in the reliability of the boost dc/dc converter. These studies aid in choosing a configuration to improve the reliability of power electronics equipment depending on the specifications of the implemented devices.

• Earthquakes and Structures
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• v.14 no.5
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• pp.425-436
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• 2018

The design of seismically isolated structures considering the stochastic nature of excitations, base isolators' design parameters, and superstructure properties requires robust reliability analysis methods to calculate the failure probability of the entire system. Here, by applying artificial neural networks, we proposed a robust technique to accelerate the estimation of failure probability of equipped isolated structures. A three-story isolated building with susceptible facilities is considered as the analytical model to evaluate our technique. First, we employed a sensitivity analysis method to identify the critical sources of uncertainty. Next, we calculated the probability of failure for a particular set of random variables, performing Monte Carlo simulations based on the dynamic nonlinear time-history analysis. Finally, using a set of designed neural networks as a surrogate model for the structural analysis, we assessed once again the probability of the failure. Comparing the obtained results demonstrates that the surrogate model can attain precise estimations of the probability of failure. Moreover, our proposed approach significantly increases the computational efficiency corresponding to the dynamic time-history analysis of the structure.