• Journal of Advanced Marine Engineering and Technology
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• v.27 no.7
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• pp.930-936
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• 2003

A new method of direct current motor drive, which requires neither shaft encoder nor speed estimator, is presented. The proposed scheme is based on decreasing current gap between a numerical model and an actual motor. By supplying the identical instantaneous voltage to both model and motor in the direction of reducing the current difference, the rotor approaches to the model speed, that is, reference value. The performance of direct current motor drives without speed sensor is generally poor at very low speed. However, in this system, it is possible to obtain good speed performance in the low speed range.

• Journal of Korean Society for Quality Management
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• v.22 no.3
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• pp.99-110
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• 1994

The strength-stress model has been widely used in a variety of areas including testing the reliability of the item or design procedures. This model was first introduced in 1950's and can be found on various applications in civil, aerospace engineering etc. This paper considers the strength-stress model in detail and proposes an estimator which deals with the reliability estimation problem based on censored observations in the strength variables.

• Journal of Sensor Science and Technology
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• v.32 no.6
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• pp.475-480
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• 2023

When modeling a sensor system mathematically, we assume that the sensor noise is Gaussian and white to simplify the model. If this assumption fails, the performance of the sensor model-based controller or estimator degrades due to incorrect modeling. In practice, non-Gaussian or non-white noise sources often arise in many digital sensor systems. Additionally, the noise parameters of the sensor model are not known in advance without additional noise statistical information. Moreover, disturbances or high nonlinearities often cause unknown sensor modeling errors. To estimate the uncertain noise and model parameters of a sensor system, this paper proposes an iterative batch calibration method using data-driven machine learning. Our simulation results validate the calibration performance of the proposed approach.

• Journal of The Korean Digital Architecture Interior Association
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• v.10 no.3
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• pp.11-18
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• 2010

Cost estimation through fast and correct quantity take offs are crucial in the process of construction project. The existing methods for cost estimation are mainly based on 2D-based drawings and the estimation result tends to be different according to the estimator's experience, the quality and quantity of used information and estimation time. To solve these problems, the domestic construction industry have recently tried to use the data extracted from 3D data modeling based on BIM(Building Information Modeling) in order to achieve more accurate and objective cost estimation. However it tends to increase dramatically the quantity of information that can be used in cost estimation by estimators. Therefore in order to achieve quality information data from 3D data modeling, the characteristics of the project should be reflected on the 3D model and it is most important to extract information only for cost estimation from the whole 3D model fast and accurately. Thus this study aims to propose the 3D modeling method through Data Normalization which maximizes the usability of 3D Data modeling in cost estimation process.

• Communications for Statistical Applications and Methods
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• v.31 no.5
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• pp.497-519
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• 2024

In reliability analysis, the probability P(Y < X) is significant because it denotes availability and dependability in a stress-strength model where Y and X are the stress and strength variables, respectively. In reliability theory, the inverse Lomax distribution is a well-established lifetime model, and the literature is developing inference techniques for its reliability attributes. In this article, we are interested in estimating the stress-strength reliability R = P(Y < X), where X and Y have an unknown common scale parameter and follow the inverse Lomax distribution. Using Bayesian and non-Bayesian approaches, we discuss this issue when both stress and strength are expressed in terms of lower record values. The parametric bootstrapping techniques of R are taken into consideration. The stress-strength reliability estimator is investigated using uniform and gamma priors with several loss functions. Based on the proposed loss functions, the reliability R is estimated using Bayesian analyses with Gibbs and Metropolis-Hasting samplers. Monte Carlo simulation studies and real-data-based examples are also performed to analyze the behavior of the proposed estimators. We analyze electrical insulating fluids, particularly those used in transformers, for data sets using the stress-strength model. In conclusion, as expected, the study's results showed that the mean squared error values decreased as the record number increased. In most cases, Bayesian estimates under the precautionary loss function are more suitable in terms of simulation conclusions than other specified loss functions.

• Communications for Statistical Applications and Methods
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• v.14 no.2
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• pp.389-399
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• 2007

In this paper, Bayes estimates for the parameters k, c and reliability function of the Burr type XII model based on a type II censored samples under asymmetric loss functions viz., LINEX and SQUAREX loss functions are obtained. An approximation based on the Laplace approximation method (Tierney and Kadane, 1986) is used for obtaining the Bayes estimators of the parameters and reliability function. In order to compare the Bayes estimators under squared error loss, LINEX and SQUAREX loss functions respectively and the maximum likelihood estimator of the parameters and reliability function, Monte Carlo simulations are used.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2516-2520
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• 2005

In this paper, finite impulse response (FIR) smoothers are proposed for discrete-time systems. The proposed FIR smoother is designed under the constraints of linearity, unbiasedness, FIR structure, and independence of the initial state information. It is also obtained by directly minimizing the performance criterion with unbiased constraints. The approach to the MVF smoother proposed in this paper is logical and systematic, while existing results have heuristic assumption, such as infinite covariance of the initial state. Additionally, the proposed MVF smoother is based on the general system model that may have the singular system matrix and has both system and measurement noises. Thorough simulation studies, it is shown that the proposed MVF smoother is more robust against modeling uncertainties numerical errors than fixed-lag Kalman smoother which is infinite impulse response (IIR) type estimator.

• Journal of the Korean Data and Information Science Society
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• v.25 no.4
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• pp.903-914
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• 2014

The inverse Weibull distribution has been proposed as a model in the analysis of life testing data. Also, inverse Weibull distribution has been recently derived as a suitable model to describe degradation phenomena of mechanical components such as the dynamic components (pistons, crankshaft, etc.) of diesel engines. In this paper, we derive the approximate maximum likelihood estimators of the scale parameter and the shape parameter in the inverse Weibull distribution under multiply type-II censoring. We also develop four modified empirical distribution function (EDF) type tests for the inverse Weibull or extreme value distribution based on multiply type-II censored samples. We also propose modified normalized sample Lorenz curve plot and new test statistic.

• Journal of Mechanical Science and Technology
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• v.19 no.4
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• pp.985-992
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• 2005

Vehicle Stability Control (VSC) system prevents vehicle from spinning or drifting out mainly by braking intervention. Although a control threshold of conventional VSC is designed by vehicle characteristics and centered on average drivers, it can be a redundancy to expert drivers in critical driving conditions. In this study, a manual adaptation of VSC is investigated by changing the control threshold. A control threshold can be determined by phase plane analysis of side slip angle and angular velocity which is established with various vehicle speeds and steering angles. Since vehicle side slip angle is impossible to be obtained by commercially available sensors, a side slip angle is designed and evaluated with test results. By using the estimated value, phase plane analysis is applied to determine control threshold. To evaluate an effect of control threshold, we applied a 23-DOF vehicle nonlinear model with a vehicle planar motion model based sliding controller. Controller gains are tuned as the control threshold changed. A VSC with various control thresholds makes VSC more flexible with respect to individual driver characteristics.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.1
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• pp.29-36
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• 2014

In this paper, a novel MBE (Model Based target size Estimator) is presented for SDIIR (Strap Down Imaging Infrared) seekers. The target tracking requires the target size information for which residual range between target and missile should be provided. Unfortunately, in general, the missile with passive sensor such as IIR (Imaging Infrared), CCD (Coupled Charging Device) cannot obtain range information. To overcome the problem, the proposed method enables the SDIIR seeker to estimates target size by using target size model and track the target. The performance of proposed method is tested at IIR target tracking of target intercept scenario. The experiment results show that the proposed algorithm has the relatively good performance.