• Structural Engineering and Mechanics
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• v.17 no.1
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• pp.29-50
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• 2004

A total life model was developed to assess the service life of aging aircraft. The primary focus of this paper is the development of crack growth life projection using the response surface method. Crack growth life projection is a necessary component of the total life model. The study showed that the number of load cycles N needed for a crack to propagate to a specified size can be linearly related to the geometric parameter, material, and stress level of the component considered when all the variables are transformed to logarithmic values. By the Central Limit theorem, the ln N was approximated by Gaussian distribution. This Gaussian model compared well with the histograms of the number of load cycles generated from simulated crack growth curves. The outcome of this study will aid engineers in designing their crack growth experiments to develop the stochastic crack growth models for service life assessments.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.1
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• pp.40-46
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• 2000

In this paper, a transient identification based on a Hidden Markov Model (HMM) has been suggested and evaluated experimentally for the classification of transients in the dynamic process. The transient can be identified by its unique time dependent patterns related to the principal variables. The HMM, a double stochastic process, can be applied to transient identification which is a spatial and temporal classification problem under a statistical pattern recognition framework. The HMM is created for each transient from a set of training data by the maximum-likelihood estimation method. The transient identification is determined by calculating which model has the highest probability for the given test data. Several experimental tests have been performed with normalization methods, clustering algorithms, and a number of states in HMM. Several experimental tests have been performed including superimposing random noise, adding systematic error, and untrained transients. The proposed real-time transient identification system has many advantages, however, there are still a lot of problems that should be solved to apply to a real dynamic process. Further efforts are being made to improve the system performance and robustness to demonstrate reliability and accuracy to the required level.

• Journal of the Korea Concrete Institute
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• v.17 no.6 s.90
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• pp.1045-1051
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• 2005

For critical structures and application, where a given reliability must be met, it is necessary to account for uncertainties and variability in material properties, structural parameters affecting the corrosion process, in addition to the statistical and decision uncertainties. This paper presents an approach to the fuzzy arithmetic based modeling of the chloride-induced corrosion of reinforcement in concrete structures that takes into account the uncertainties in the physical models of chloride penetration into concrete and corrosion of steel reinforcement, as well as the uncertainties in the governing parameters, including concrete diffusivity, concrete cover depth, surface chloride concentration and critical chloride level for corrosion initiation. The parameters of the models are regarded as fuzzy numbers with proper membership function adapted to statistical data of the governing parameters and the fuzziness of the corrosion time is determined by the fuzzy arithmetic of interval arithmetic and extension principle

• Journal of Korean Institute of Industrial Engineers
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• v.21 no.1
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• pp.17-32
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• 1995

The objective of this study is to develop a general design and performance evaluation model for the system designers in the initial design phase of the integrated automatic manufacturing system based on the RAM(Reliability, Availability and Maintainability) and life cycle cost(LCC). The methodology proposed in this research includes the following two stages. First, a deterministic approach to the solution of optimal work station arrangement for the initial system configuration is considered under the assumption that the system availability is one(no failure and maintenance), and then a stochastic simulation model based on RAM and LCC is developed. Using the results of these two stage simulation, a system performance index(SPI) was developed for the performance evaluation of the proposed system. Also a computer program is developed.

• Proceedings of the KIEE Conference
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• 2008.04b
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• pp.171-173
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• 2008

This paper presents stochastic methodology based fault diction and diagnosis algorithm for induction motor systems. First, we construct probability distribution model from healthy motors and then probability distribution for faulty motors is recursively calculated by means of the proposed probability estimation. We measure motor current with hall sensors as system state. The estimated probability is compared to the model to generate a residue signal which is utilized for fault detection and diagnosis, that is, where a fault is occurred. We carry out real-time induction motor experiment to evaluate efficiency and reliability of the proposed approach.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1503-1504
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• 2008

This paper presents stochastic methodology based fault diction and diagnosis algorithm for induction motor systems. First, we construct probability distribution model from healthy motors and then probability distribution for faulty motors is recursively calculated by means of the proposed probability estimation. We measure motor current with hall sensors as system state. The estimated probability is compared to the model to generate a residue signal which is utilized for fault detection and diagnosis, that is, where a fault is occurred. We carry out real-time induction motor experiment to evaluate efficiency and reliability of the proposed approach.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2007.05a
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• pp.328-333
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• 2007

Traditional maintenance planning is based on a constant maintenance interval for equipment life. In order to consider economic aspect for tm based preventive maintenance, preventive maintenance is desirable to be scheduled by RCM(Reliability-Centered Maintenance) evaluation. The main objective of RCM is to reduce the maintenance cost, by focusing on the most important functions of the system and avoiding or removing maintenance actions that are not strictly necessary. So, Markov state model is utilized considering stochastic state in RCM In this paper, a Markov state model much can be used for scheduling and optimization of maintenance is presented. The deterioration process of system condition is modeled by the stepwise Markov model in detail. Also, because the system is not continuously monitored, the inspection is considered. In case study, simulation results about RCM will be shown using the real historical data of combustion turbine generating unit in Korean power systems.

• Journal of Korea Water Resources Association
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• v.51 no.10
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• pp.887-893
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• 2018

In this study, the optimum design technology is suggested by using reliability analysis method. Nowadays, urban flood inundation is easily occurred because of local heavy rain. Traditional deterministic design method for storm sewer may underestimate the size of pipe. Therefore, stochastic method for the storm sewer design is necessary to solve this problem. In the present study, reliability model using FORM (First Order Reliability Method) was developed for the storm sewer. Developed model was applied to the real storm sewers of 5 different areas. Probability of exceeding capacity has been calculated and construction costs according to diameter have been compared. Probability of exceeding capacity of storm sewers of 5 areas have been calculated after estimating the return period of rainfall intensity.

• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.5
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• pp.596-604
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• 2016

In this study, we used a stochastic approach for guaranteeing the reliability and robustness of the performance with regard to the design of polymer components, while taking into consideration the degradation properties and operating conditions in automobiles. Creep and tensile tests were performed for obtaining degradation properties. The Prony series, which described the viscoelastic models, were calculated to use the creep data by the Maxwell fluid model. We obtained the stress data from the frequency response analysis of the polymer components while considering the degradation properties. Limit state functions are generated by using these data. Reliability assessments are conducted under the variation of the degradation properties and area of frequency at peak response. For this study, the input parameters are assumed to be a normal distribution, and the reliability under the yield stress criteria is evaluated by using the Monte Carlo Simulation. As a result, the reliabilities, according to the three types of polymer materials in automotive components, are compared to each other and suggested the applicable possibility of polymeric materials in automobiles.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.1
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• pp.23-33
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• 1994

In this paper, we propose a probabilistic model appropriate for the bearing estimator which uses cross-correlation method following a close investigation on real underwater acoustic bearing data. The well-known JPDA(Joint Probabilistic Data Association) filter is tuned to the underwater acoustic bearing estimation based on the result that the reliability of the bearing measurement is related to the amplitude of the cross-correlation peak. The proposed probabilistic model is shown to be adequate by presenting the results of the improved tracking performance of the modified filter for various real bearing data as well as artificially generated ones.