• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.11
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• pp.1758-1764
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• 2012

A large number of wire rope has been used in various inderstiries as Cranes and Elevators from expanding the scale of the industrial market. But now, the management of wire rope is used as manually operated by rope replacement from over time or after the accident.It is caused to major accidents as well as economic losses and personal injury. Therefore its time to need periodic fault diagnosis of wire rope or supply of real-time monitoring system. Currently, there are several methods has been reported for fault diagnosis method of the wire rope, to find out the feature point from extracting method is becoming more common compared to time wave and model-based system. This method has implemented a deterministic modeling like the observer and neural network through considering the state of the system as a deterministic signal. However, the out-put of real system has probability characteristics, and if it is used as a current method on this system, the performance will be decreased at the real time. And if the random noise is occurred from unstable measure/experiment environment in wire rope system, diagnostic criterion becomes unclear and accuracy of diagnosis becomes blurred. Thus, more sophisticated techniques are required rather than deterministic fault diagnosis algorithm. In this paper, we developed the fault diagnosis of the wire rope using probability density estimation techniques algorithm. At first, The steady-state wire rope fault signal detection is defined as the probability model through probability distribution estimate. Wire rope defects signal is detected by a hall sensor in real-time, it is estimated by proposed probability estimation algorithm. we judge whether wire rope has defection or not using the error value from comparing two probability distribution.

• Structural Engineering and Mechanics
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• v.57 no.1
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• pp.21-43
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• 2016

A conditional probability based approach known as Particle Filter Method (PFM) is a powerful tool for system parameter identification. In this paper, PFM has been applied to identify the vehicle parameters based on response statistics of the bridge. The flexibility of vehicle model has been considered in the formulation of bridge-vehicle interaction dynamics. The random unevenness of bridge has been idealized as non homogeneous random process in space. The simulated response has been contaminated with artificial noise to reflect the field condition. The performance of the identification system has been examined for various measurement location, vehicle velocity, bridge surface roughness factor, noise level and assumption of prior probability density. Identified vehicle parameters are found reasonably accurate and reconstructed interactive force time history with identified parameters closely matches with the simulated results. The study also reveals that crude assumption of prior probability density function does not end up with an incorrect estimate of parameters except requiring longer time for the iterative process to converge.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.2
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• pp.231-235
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• 2013

The purpose of this paper is to compare with estimation of equivalent fatigue load in time domain and frequency domain and estimate the fatigue life of structure with multi-axial vibration loading. The fatigue analysis with two methods is implemented with various signals like random, sinusoidal signals. Also an equivalent fatigue life estimated by rainflow cycle counting in time domain is compared with results estimated with probability density function of each signal in frequency domain. In case of frequency domain, equivalent fatigue life can estimate through Dirlik's method with probability density function. And the work proposed in this paper compared the fatigue damage accumulated under uni-axial loading to that induced by multi-axial loading. The comparison is preformed for a simple cantilever beam, which is exposed to vibrations of several directions. For verification of estimation performance of fatigue life, results are compared to those of FEM analysis (ANSYS).

• The Transactions of the Korea Information Processing Society
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• v.5 no.5
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• pp.1119-1129
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• 1998

This paper proposes a method to estimate the time to execute a hypermedia scenario. The method builds a PNDT(Petri Net with probability Distribution Table) model for the flow of the scenario, then performs Monte Carlo Simulation on the PNDT model to estimate the duration time from the start to the end of the scenario. The estimated times to execute scenarios are useful to both information providers and users. A user can make a better time plan referring to them, and an information provider can make the most efficient scenario-presentation schedule for users referring to them. However, no research results regarding this subject have been reported yet.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.4A
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• pp.227-238
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• 2012

In this paper, we propose a practical time-division half-duplex Estimate and Forward (EF) relaying protocol. The conventional EF relaying protocol works well only when the relay node is near the destination node. The proposed EF relaying protocol, however, determines adaptively relay parameters such as the quantization level of relay node and the power allocation between source and relay nodes according to the channel conditions. By doing so, the proposed EF relaying protocol provides low probability of bit error even when the relay node is far from the destination node. Consequently, the proposed EF protocol is suitable for the mobile relay systems. It is shown by simulations that the proposed EF relaying protocol shows lower bit error rate for all relay positions than a conventional EF protocol.

• Journal of Korean Institute of Industrial Engineers
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• v.4 no.1
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• pp.29-32
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• 1978

We obtain the minimum variance unbiased estimate of system reliability when a system consists of n components whose life times are assumed to be independent and identically distributed either negative exponential or geometric random variables. For the case of a negative exponential life time, we obtain the minimum variance unbiased estimate of the probability density function of the i-th order statistic.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.508-518
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• 2008

Reliability and sensitivity analysis of the design parameters for a section of caisson type quaywall which is the most applicable in Korea were performed. It was tried to estimate probabilities of failure for the system of the multiple failure modes and to analyze LCC in the quaywall structure. The reliability analysis was performed by FORM. Also, sensitivity indices were estimated using the reliability indices, which may be used inferring effects of each design parameter on the reliability indices. As a result, the coefficient of friction between caisson and rubble, the moment by self weight and the moment of resistance mostly affected on the reliability indices in the sliding, overturning and foundation failure, respectively. System reliability theorem was applied in order to estimate the probabilities of failure for the system of the multiple failure modes. As the results of estimation of the probabilities of failure for the system, all cases were more conservative than those for the elements, according to both failure mode and load combination applied to series system. It entirely exceeded the target reliability index, but it was consistent with the theorem. According to the optimum LCC with the width of the caisson, the probability of failure exceeded the target probability of failure at then time. Therefore, it was judged to be insufficient to the practical application.

• Wind and Structures
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• v.33 no.6
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• pp.423-435
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• 2021

Although existing algorithms can predict wind speed using historical observation data, for engineering feasibility, most use moment methods and probability density functions to estimate fitted parameters. However, extreme wind speed prediction accuracy for long-term return periods is not always dependent on how the optimized frequency distribution curves are obtained; long-term return periods emphasize general distribution effects rather than marginal distributions, which are closely related to potential extreme values. Moreover, there are different wind speed parent sample types; how to theoretically select the proper extreme value distribution is uncertain. The influence of different sampling time intervals has not been evaluated in the fitting process. To overcome these shortcomings, updated steps are introduced, involving parameter sensitivity analysis for different sampling time intervals. The extreme value prediction accuracy of unknown parent samples is also discussed. Probability analysis of mean wind is combined with estimation of the probability plot correlation coefficient and the maximum likelihood method; an iterative estimation algorithm is proposed. With the updated steps and comparison using a Monte Carlo simulation, a fitting policy suitable for different parent distributions is proposed; its feasibility is demonstrated in extreme wind speed evaluations at Longhua and Chuansha meteorological stations in Shanghai, China.

• Tunnel and Underground Space
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• v.20 no.1
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• pp.39-48
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• 2010

The present study developed a program which can assess the reliability of tunnel support systems based on a probability-based method. The developed program uses FLAC2D as a solver, and can automatically execute all the processes, associated with numerical and probabilistic analysis. Since a numerical analysis, which models the ground, requires a significant calculation time, it is actually impossible to apply simulation-based methods to probabilistic assessment on the reliability of tunnel support systems. Therefore, the present study used a point estimate method, which is efficient for probabilistic analysis since the method can significantly reduce the number of samples when compared with the simulation-based method. The developed program was applied to a tunnel project, and the results were compared with those through a deterministic approach. From the comparison, it was identified that a probabilistic approach can quantitatively assess the reliability of tunnel support systems based on probability of failure and can be used as a tool for decision making in tunnel support designs.

• Earthquakes and Structures
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• v.14 no.5
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• pp.437-447
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• 2018

Computational cost is one of the major obstacles for detailed risk analysis of structures. This paper puts forward a methodology for efficient probabilistic seismic loss assessment of structures using the Endurance Time (ET) analysis and the first-order reliability method (FORM). The ET analysis efficiently yields the structural responses for a continuous range of intensities through a single response-history analysis. Taking advantage of this property of ET, FORM is employed to estimate the annual rate of exceedance for the loss components. The proposed approach is an amalgamation of two analysis approaches, ET and FORM, that significantly lower the computational costs. This makes it possible to evaluate the seismic risk of complex systems. The probability distribution of losses due to the structural and non-structural damage as well as injuries and fatalities of a prototype structure are estimated using the proposed methodology. This methodology is an alternative to the prevalent risk analysis framework of the total probability theorem. Hence, the risk estimates of the proposed approach are compared with those from the total probability theorem as a benchmark. The results indicate a satisfactory agreement between the two methods while a significantly lower computational demand for the proposed approach.