• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권10호
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• pp.5095-5111
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• 2016

The Probability Hypothesis Density (PHD) filter is a suboptimal approximation and tractable alternative to the multi-target Bayesian filter based on random finite sets. However, the PHD filter fails to track newborn targets when the target birth intensity is unknown prior to tracking. In this paper, a dual detection-guided newborn target intensity PHD algorithm is developed to solve the problem, where two schemes, namely, a newborn target intensity estimation scheme and improved measurement-driven scheme, are proposed. First, the newborn target intensity estimation scheme, consisting of the Dirichlet distribution with the negative exponent parameter and target velocity feature, is used to recursively estimate the target birth intensity. Then, an improved measurement-driven scheme is introduced to reduce the errors of the estimated number of targets and computational load. Simulation results demonstrate that the proposed algorithm can achieve good performance in terms of target states, target number and computational load when the newborn target intensity is not predefined in multi-target tracking systems.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 춘계학술대회 논문집 전기설비전문위원
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 제39회 하계학술대회
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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.

• Structural Engineering and Mechanics
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• 제28권4호
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• pp.373-386
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• 2008

In this study stochastic analysis of non-linear dynamical systems under ${\alpha}$-stable, multiplicative white noise has been conducted. The analysis has dealt with a special class of ${\alpha}$-stable stochastic processes namely sub-Gaussian white noises. In this setting the governing equation either of the probability density function or of the characteristic function of the dynamical response may be obtained considering the dynamical system forced by a Gaussian white noise with an uncertain factor with ${\alpha}/2$- stable distribution. This consideration yields the probability density function or the characteristic function of the response by means of a simple integral involving the probability density function of the system under Gaussian white noise and the probability density function of the ${\alpha}/2$-stable random parameter. Some numerical applications have been reported assessing the reliability of the proposed formulation. Moreover a proper way to perform digital simulation of the sub-Gaussian ${\alpha}$-stable random process preventing dynamical systems from numerical overflows has been reported and discussed in detail.

• Journal of Advanced Marine Engineering and Technology
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• 제23권4호
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• pp.453-461
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• 1999

The estimation of fatigue life at the design stage is very important in order to arrive at feasible and cost effective solutions considering the total lifetime of the structure and machinery compo-nents. In this study the practical procedure of prediction of fatigue life by use of cumulative damage factors based on Miner-Palmgren hypothesis and probability density function is shown with a $135,000m^3$ LNG tank being used as an example. In particular the parameters of Weibull distribution taht determine the stress spectrum are dis-cussed. At the end some of uncertainties associated with fatigue life prediction are discussed. The main results obtained from this study are as follows: 1. The practical procedure of prediction of fatigue life by use of cumulative damage factors expressed in combination of probability density function and S-N data is proposed. 2. The calculated fatigue life is influenced by the shape parameter and stress block. The conser-vative fatigue design can be achieved when using higher value of shape parameter and the stress blocks divded into more stress blocks.

• Journal of the Korean Data and Information Science Society
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• 제20권1호
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• pp.191-202
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• 2009

In this study, we drive the one dimensional marginal transform function, probability density function and probability distribution function for the random variables $T_{{\xi}N}$ (Time taken by the servers during the vacations), ${\xi}_N$(Number of vacations taken by the servers) and ${\eta}_N$(Number of customers or units arrive in the system) by controlling the variability of two random variables simultaneously.

• Journal of Information Processing Systems
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• 제15권2호
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• pp.331-343
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• 2019

Dynamic thermal rating of the overhead transmission lines is affected by many uncertain factors. The ambient temperature, wind speed and wind direction are the main sources of uncertainty. Measurement uncertainty is an important parameter to evaluate the reliability of measurement results. This paper presents the uncertainty analysis based on Monte Carlo. On the basis of establishing the mathematical model and setting the probability density function of the input parameter value, the probability density function of the output value is determined by probability distribution random sampling. Through the calculation and analysis of the transient thermal balance equation and the steady- state thermal balance equation, the steady-state current carrying capacity, the transient current carrying capacity, the standard uncertainty and the probability distribution of the minimum and maximum values of the conductor under 95% confidence interval are obtained. The simulation results indicate that Monte Carlo method can decrease the computational complexity, speed up the calculation, and increase the validity and reliability of the uncertainty evaluation.

• Journal of the Korean Data and Information Science Society
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• 제25권3호
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• pp.623-632
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• 2014

We shall consider the estimation for the parameter and the right tail probability in a general exponential distribution. We also shall consider the estimation of the reliability P(X < Y ) and the skewness trends of the density function of the ratio X=(X+Y) for two independent general exponential variables each having different shape parameters and known scale parameter. We then shall consider the estimation of the failure rate average and the hazard function for a general exponential variable having the density function with the unknown shape and known scale parameters, and for a bivariate density induced by the general exponential density.

• 전자공학회논문지S
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• 제34S권2호
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• pp.79-93
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• 1997

This paper presents a linear shift-invariant system euqivalent to morphological dilation for a memoryless uniform source in the sense of the power spectral density function, and comares it with dialtion. This equivalent LSI system is found through spectral decomposition and, for dilation and with windwo size L, it is shown to be a finite impulse response filter composed of L-1 delays, L multipliers and three adders. Th ecoefficients of the equivalent systems are tabulated. The comparisons of dilation and its equivalent LSI system show that probability density functions of the output sequences of the two systems are quite different. In particular, the probability density functon from dilation of an independent and identically distributed uniform source over the unit interval (0, 1) shows heavy probability in around 1, while that from the equivalent LSI system shows probability concentration around themean vlaue and symmetricity about it. This difference is due to the fact that dilation is a non-linear process while the equivalent system is linear and shift-ivariant. In the case that dikation is fabored over LSI filters in subjective perforance tests, one of the factors can be traced to this difference in the probability distribution.

• 한국도로학회논문집
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• 제19권5호
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• pp.89-96
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• 2017

PURPOSES: This study aims to develop a rational procedure for estimating the pavement roughness index considering vehicle wandering. METHODS : The location analysis of the passing vehicle in the lane was performed by approximately 1.2 million vehicles for verification of the wandering distribution. According to verification result, the distribution follows the normal distribution pattern. The probability density function was estimated using each lane's wandering distribution model. Then the procedure for applying a weighted value into the lane profile was conducted using this function. RESULTS : The modified index, MRIw, with consideration towards applying the wandering weighted value application was computed then compared with MRI. It was found that the Coefficient of Variation for distribution of lateral roughness index in the lane was high in the case of a large difference between each index (i.e., MRIw and MRI) observed. CONCLUSIONS : This result confirms that the new procedure with consideration of the weight factor can successfully improve the lane representative characteristics of the roughness index.