• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.16 no.3
• /
• pp.2172-2177
• /
• 2015

The DF-MZEP-CME (decision feedback - maximum zero-error probability for constant modulus errors) algorithm that makes the probability for constant modulus error (CME) close to zero and employs decision feedback (DF) structures shows more improved performance in channel distortion compensation. However the DF-MZEP-CME algorithm has a computational complexity proportional to a sample size for probability estimation and this property plays a role of an obstacle in practical implementation. In this paper, the gradient of DF-MZEP-CME is proposed to be estimated recursively and shown to solve the computational problem by making the algorithm independent of the sample size. For a sample size N, the conventional method has 10N multiplications but the proposed has only 20 regardless of N. Also the recursive gradient estimation for weight update is kept in continuity from the initial state to the steady state without any error propagation.

• Journal of Korean Society of Disaster and Security
• /
• v.6 no.2
• /
• pp.23-30
• /
• 2013

A dynamic analysis of random vibration processes is concerned with the first excursion probability based on first passage time during some specified lifetime or duration of the excitation. This study is concerned with the estimation of first-passage probability for hazard fluctuate wind velocity in the major cities reflecting the recent meteorological with largest data samples (yearly 2003-2012). The basic wind speeds were standardized homogeneously to the surface roughness category C, and to 10m above the ground surface. In this paper, the hazard fluctuate wind velocities are treated as a time-independent (stationary) random process and Gaussian random processes. The first excursion probability were calculated from Poisson model based on the independent event of level crossing & two-state Markov model based on the envelopes of level crossing.

• Journal of the Korean Society of Safety
• /
• v.35 no.5
• /
• pp.30-38
• /
• 2020

In order to construct a dam, the diversion facility such as cofferdam and a diversion tunnel should be installed in advance. And size of a cofferdam depends on type of a main dam. According to the Korea Dam Design Standard, if the main dam is a concrete dam, design flood of the cofferdam is 1~2 years flood frequency. This means that overflow of the cofferdam occurs one time for 1 or 2 years, therefore, stability of the cofferdam should be secured against any overflow problem. In this study, failure probability analysis for the concrete cofferdam is performed considering the overflow. First of all, limit state function of the concrete cofferdam is defined for overturning, sliding and base pressure, and upstream water levels are set as El. 501 m, El. 503 m, El. 505 m, El. 507 m. Also, after literature investigation research, probabilistic characteristics of various random variables are determined, the failure probability of the concrete cofferdam is calculated using the Monte Carlo Simulation. As a result of the analysis, when the upstream water level rises, it means overflow, the failure probability increases rapidly. In particular, the failure probability is largest in case of flood loading condition. It is considered that the high upstream water level causes increase of the upstream water pressure and the uplift pressure on the foundation. In addition, among the overturning, the sliding and the base pressure, the overturing is the major cause for the cofferdam failure considering the overflow.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.25 no.6
• /
• pp.447-458
• /
• 2023

In this study, a comparison model considering the stochastic characteristics of the load and member resistance of the shield tunnel segment lining as well as the variability of the boundary condition was selected and reliability analysis was performed, and the adequacy of the limit state design was analyzed by calculating the probability of failure and reviewing the structural safety. For the analysis considering the probability characteristics of these ground constants, the ground spring coefficient was considered as the mean value by calculating the quantitative value by applying the Muirwood formula, and the coefficient of variation was selected based on the existing research data to review the models according to the change of ground boundary conditions. Through the structural analysis of these models and the reliability analysis using MCS technique, the failure probability and reliability index were calculated to examine the changes in the failure probability due to changes in ground boundary conditions.

• Journal of applied mathematics & informatics
• /
• v.25 no.1_2
• /
• pp.389-405
• /
• 2007

In this paper, we study a k-out-of-n system with single server who provides service to external customers also. The system consists of two parts:(i) a main queue consisting of customers (failed components of the k-out-of-n system) and (ii) a pool (of finite capacity M) of external customers together with an orbit for external customers who find the pool full. An external customer who finds the pool full on arrival, joins the orbit with probability ${\gamma}$ and with probability $1-{\gamma}$ leaves the system forever. An orbital customer, who finds the pool full, at an epoch of repeated attempt, returns to orbit with probability ${\delta}\;(<\;1)$ and with probability $1-{\delta}$ leaves the system forever. We compute the steady state system size probability. Several performance measures are computed, numerical illustrations are provided.

• Proceedings of the KIEE Conference
• /
• 2008.04a
• /
• pp.228-229
• /
• 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
• /
• 2008.04b
• /
• pp.171-173
• /
• 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 Society of Precision Engineering Conference
• /
• 2003.06a
• /
• pp.1557-1560
• /
• 2003

This paper presents the effect of varying boundary conditions such as ground subsidence on failure prediction of buried pipelines. The first order Taylor series expansion of the limit state function is used in order to estimate the probability of failure associated with three cases of ground subsidence. We estimate the distribution of stresses imposed on the buried pipelines by varying boundary conditions and calculate the probability of pipelines with von-Mises failure criterion. The effects of random variables such as pipe diameter, internal pressure, temperature, settlement width, load for unit length of pipelines, material yield stress and thickness of pipeline on the failure probability of the buried pipelines are also systematically studied by using a failure probability model for the pipeline crossing a ground subsidence region.

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

• Journal of Advanced Navigation Technology
• /
• v.23 no.5
• /
• pp.352-360
• /
• 2019

This paper proposes a docking assessment algorithm for an autonomous underwater vehicles (AUVs) with sensor uncertainties. The proposed algorithm consists of two assessments, state assessment and probability assessment. The state assessment verifies the reachability by comparing forward distance to the docking station with expected distance to reach same depth as the docking station and necessity for correcting its route by comparing calculated inaccessible areas based on turning radius of the AUV to position of the docking station. When the AUV and the docking station is close enough and the state assessment is satisfied, the probability assessment is conducted by computing success probability of docking based on the direction angle, relative position to the docking station, and sensor uncertainties of the AUV. The final output of the algorithm is decided by comparing the success probability to threshold whether to try docking or to correct its route. To verify the validation of the suggested algorithm, the scenario that the AUV approaches to the docking station is implemented through Matlab simulation.