• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.2
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• pp.125-132
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• 2015

This paper is about analysis of UDRE monitoring method for Korean Satellite navigation system, which is the correction parameter of satellite measurements. New receiver clock bias and tropospheric delay error estimation method to make pseudo-range residual for UDRE monitoring is proposed. Saastamoinen model and Neill mapping function are used for estimate the tropospheric delay and EKF is used for estimgate the receiver clock bias. Through the satellite measurements and regional weather data received directly from the domestic is using for UDRE monitoring analysis, more suitable UDRE monitoring threshold can be deducted and it is expected to be utilized for fault detection technique of Korean Satellite Navigation System.

• Journal of the Korean Society for Railway
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• v.12 no.4
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• pp.535-541
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• 2009

The reliability of control system composed of electronic parts has been studied by DoD since 1960, and has been undertaken mainly by Europe for railways. Especially in Korea, a study on reliability of signalling equipment has been taken since 2000, requiring reliability test for effective maintenance of old type signalling equipment which no longer has information on its past reliability. This study evaluates the reliability test in units of parts for old type signalling equipment; for instance, failure rate in units of parts, or failure data during operation; which was utilized without its consistent reliability monitoring and analysis data for over 20 years. Also, reliability change at this point in time has been estimated by using residual life span function, and a model which can evaluate the possibility of extended operation through stress acceleration test has been developed. This model will be utilized to establish future maintenance policy for train operating company's operation on old type signalling equipment.

• Communications for Statistical Applications and Methods
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• v.15 no.3
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• pp.387-402
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• 2008

In this thesis we propose a two-stage periodic inspection model for maintaining the reliability of a system in long-term storage. There are two types of tests available; a fallible test and an error-free test. The system is overhauled at detection of failure or when the storage reliability after inspection becomes less than or equal to the prespecified value. The expected cost per unit time until overhaul is derived and a procedure for minimizing the expected cost is suggested. The two-stage periodic inspection model is compared with the one-stage periodic inspection model for various parameters of the cost function when the failure time follows exponential and Weibull distributions. The proposed model is then applied to an existing missile system for comparison with the current inspection policy.

• Nuclear Engineering and Technology
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• v.21 no.1
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• pp.1-11
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• 1989

Numerous losses of decay heat removal capability have occurred at U during stutodwn while its significance to safety is needless to say. A study is carried out as an attempt to assess what could be done to lower the frequency of these events and to mitigate their consequences in the unlikely event that one occurs. The shutdown risk model is developed and analyzed using Event/Fault Tree for the typical pressurized water reactor. The human cognitive reliability (HCR) model, two-stage bayesian approach and staircase function model are used to estimate human reliability, initiating event frequency and offsite power non-recovery probability given loss of offsite power, respectively. The results of this study indicate that the risk of a Pm at shutdown is not much lower than the risk when the plant is operating. By examining the dominant accident sequences obtained, several design deficiencies are identified and it is found that some proposed changes lead to significant reduction in core damage frequency due to loss of cooling events.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.1
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• pp.97-102
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• 2016

Since vibrations in rotating machinery is a direct cause of performance degradation and failures, it is very important to predict the level of vibrations as well as have a method to lower the vibrations to an acceptable level. However, the changes in balancing during installation and the vibrational modes of the support structure are difficult to predict. This paper presents a method for predicting the unbalanced response of a turbo-compressor supported by active magnetic bearings (AMBs). Transfer functions of the rotor are obtained through system identification using AMBs. These transfer functions contain not only the dynamics of the rotor but also the vibrational modes of the support structure. Using these transfer functions, the unbalanced response is calculated and compared with the run-up data obtained from a compressor prototype. The predictions revealed the effects of the support structure, validating the efficacy of the method.

• The KIPS Transactions:PartD
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• v.8D no.4
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• pp.393-400
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• 2001

This paper presents a stochastic model for the software failure phenomenon based on a nonhomogeneous Poisson process (NHPP). The failure process is analyzed to develop a suitable mean value function for the NHPP ; expressions are given for several performance measure. Actual software failure data are compared with generalized model by Goel dependent on the constant reflecting the quality of testing. The performance measures and parametric inferences of the new models, Rayleigh and Gumbel distributions, are discussed. The results of the new models are applied to real software failure data and compared with Goel-Okumoto and Yamada, Ohba and Osaki models. Tools of parameter inference was used method of the maximun likelihood estimate and the bisection algorithm for the computing nonlinear root. In this paper, using the sum of the squared errors, model selection was employed. The numerical example by NTDS data was illustrated.

• The KIPS Transactions:PartD
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• v.10D no.5
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• pp.805-812
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• 2003

This paper presents a stochastic model for the software failure phenomenon based on a nonhomogeneous Poisson process (NHPP) and performs Bayesian inference using prior information. The failure process is analyzed to develop a suitable mean value function for the NHPP; expressions are given for several performance measure. The parametric inferences of the model using Logarithmic Poisson model, Crow model and Rayleigh model is discussed. Bayesian computation and model selection using the sum of squared errors. The numerical results of this models are applied to real software failure data. Tools of parameter inference was used method of Gibbs sampling and Metropolis algorithm. The numerical example by T1 data (Musa) was illustrated.

• Journal of the Korean Data and Information Science Society
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• v.21 no.5
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• pp.873-882
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• 2010

This paper considers a Bayesian approach to replacement policy following the expiration of non-renewing combination warranty. The non-renewing combination warranty is the combination of the non-renewing free replacement warranty and the non-renewing pro-rata replacement warranty. We use the criterion based on the expected cost and the expected downtime to determine the optimal replacement period. To do so, we obtain the expected cost rate per unit time and the expected downtime per unit time, respectively. When the failure times are assumed to follow a Weibull distribution with uncertain parameters, we propose the optimal replacement policy based on the Bayesian approach. The overall value function suggested by Jiang and Ji (2002) is utilized to determine the optimal replacement period. Also, the numerical examples are presented for illustrative purpose.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.412-417
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• 2013

Analytical modeling of photovoltaic power systems has been receiving significant attentions in recent years in that it is easy to apply for prediction of its dynamics and fault detection and diagnosis in advanced engineering technologies. This paper presents a novel probabilistic modeling approach for such power systems with a big data sequence. Firstly, we express input/output function of photovoltaic power systems in which solar irradiation and ambient temperature are regarded as input variable and electric power is output variable respectively. Based on this functional relationship, conditional probability for these three random variables(such as irradiation, temperature, and electric power) is mathematically defined and its estimation is accomplished from ratio of numbers of all sample data to numbers of cases related to two input variables, which is efficient in particular for a big data sequence of photovoltaic powers systems. Lastly, we predict the output values from a probabilistic model of photovoltaic power systems by using the expectation theory. Two case studies are carried out for testing reliability of the proposed modeling methodology in this paper.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.10
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• pp.51-59
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• 2003

A method of autonomous update is presented for onboard orbit propagator. On board propagator is an alternative means that could be used for navigation purpose in case of CPS receiver's failure. Although the ground station is not a able to upload a new propagator, the onboard propagator must be maintained most up-to-date. For this, a filtering technique is proposed wherein GPS data are effectively used to continuously update the on board propagator which was uploaded previously. Even if the ground station has generated the on board propagator based on the wrong information, the onboard propagator with updating scheme can automatically correct the errors in the coefficients of residual reconstruction function. Several scenarios were used to show the validity of the scheme for updating the onboard propagator using KOMPSAT-1 orbit data.