• Journal of the Korea Safety Management & Science
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• v.12 no.1
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• pp.199-205
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• 2010

The research proposes the three-factor random measurement models for estimating the precision about operator, part, tool, and various measurement environments. The combined model with crossed and nested factors is developed to analyze the approximate F test by degrees of freedom given by Satterthwaite and point estimation of precisions from expected mean square. The model developed in this paper can be extended to the three useful models according to the type of nested designs. The study also provides the three-step procedures to evaluate the measurement precisions using three indexes such as SNR(Signal-To-Noise Ratio), R&R TR(Reproducibility&Repeatability-To-Total Precision Ratio), and PTR(Precision-To-Tolerance Ratio), The procedures include the identification of resolution, the improvement of R&R reduction, and the evaluation of precision effect.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.826-829
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• 2008

In a field measurement, measurement errors are produced by measuring environments and systematic errors in the measurement procedure. Measurement errors can be expressed as a measurement uncertainty. In this study, the measurement uncertainty and various measuring factors are investigated in heavy-weight impact sounds. According to KS 2810-2, the model functions, which is the estimation of the maximum SPL measurement in each octave band frequency, are determined. From this estimation model, 3.53dB is shown in 63Hz. This level is caused by the sound field of the receiving room, which does not meet the diffusing field.

• Nuclear Engineering and Technology
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• v.52 no.9
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• pp.2119-2129
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• 2020

Flow-accelerated corrosion (FAC), liquid droplet impingement erosion (LDIE), cavitation and flashing can cause continuous wall-thinning in nuclear secondary pipes. In order to prevent pipe rupture events resulting from the wall-thinning, most NPPs (nuclear power plants) implement their management programs, which include periodic thickness inspection using UT (ultrasonic test). Meanwhile, it is well known in field experiences that the thickness measurement errors (or deviations) are often comparable with the amount of thickness reduction. Because of these errors, it is difficult to estimate wall-thinning exactly whether the significant thinning has occurred in the inspected components or not. In the previous study, the authors presented an approximate estimation procedure as the first step for thickness measurement deviations at each inspected component and the statistical & quantitative characteristics of the measurement deviations using plant experience data. In this study, statistical significance was quantified for the current methods used for wall-thinning determination. Also, the authors proposed new estimation procedures for determining local wall-thinning to overcome the weakness of the current methods, in which the proposed procedure is based on analysis of variance (ANOVA) method using subgrouping of measured thinning values at all measurement grids. The new procedures were also quantified for their statistical significance. As the results, it is confirmed that the new methods have better estimation confidence than the methods having used until now.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.9
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• pp.905-912
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• 2008

Notion sickness is well known to be caused by long time exposure to the very low frequency motion in the multiple axes of human body Since the vestibular system for the perception of low frequency motion is located in the head, accurate measurement of 6 degree of freedom head motion is of great importance. In this study, the measurement system consisting of a safety helmet and 9 translational accelerometers was constructed for the estimation of 3 translational and 3 rotational motions of human head. Since estimation errors of 3 rotational components can be significantly magnified even by small offset of the sensitivity axis from the geometric center of an accelerometer, accurate measurement of sensitivity axis must be preceded. The method for accurate estimation of the offset was proposed, and the effect of offset on the estimation of angular acceleration was investigated.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.35 no.7
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• pp.261-271
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• 1986

This paper describes a method for the state estimation considering current measurement component and detection of the bad data. The state values are estimated by weighted least square method in which measurement vector included bus injection current and line current. The bad data are detected using standardized variable of normal distribution and identified using sensitivity coefficients. When the bad data were occured by the bad measurement values. The results of the application to the model power system reveal the effectiveness of the presented algorithms.

• Communications for Statistical Applications and Methods
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• v.17 no.4
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• pp.551-560
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• 2010

This paper considers a Bayesian approach to modeling a flexible regression function under structural measurement error model. The regression function is modeled based on semiparametric regression with penalized splines. Model fitting and parameter estimation are carried out in a hierarchical Bayesian framework using Markov chain Monte Carlo methodology. Their performances are compared with those of the estimators under structural measurement error model without a semiparametric component.

• Journal of the Korean Data and Information Science Society
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• v.21 no.2
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• pp.379-385
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• 2010

This paper considers Bayesian approach to modeling a flexible regression function under functional measurement error model. The regression function is modeled based on semiparametric regression with penalized splines. Model fitting and parameter estimation are carried out in a hierarchical Bayesian framework using Markov chain Monte Carlo methodology. Their performances are compared with those of the estimators under functional measurement error model without semiparametric component.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.7
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• pp.1551-1557
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• 2013

A current velocity measurement radar estimates Doppler frequencies to extract the corresponding surface velocity information. Therefore, it is required to maintain the high degree of reliability and accuracy of Doppler frequency estimates. However, Doppler spectra of water surface return echoes can have very widely varying shapes according to measurement environments and weather conditions. Therefore, serious problems may arise in maintaining the reliability and accuracy of conventional velocity estimating algorithm in a radar sensor. Therefore, in this paper, a newly suggested algorithm is proposed for improvement using estimation of peak Doppler frequencies. The proposed method shows that the more accurate velocity measurement can be possible comparing with the conventional one.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.597-598
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• 2015

In order to improve the reliability of cost estimation results using CBR, there has been a continuous issue on similarity measurement to accurately compute the distance among attributes and cases to retrieve the most similar singular or plural cases. However, these existing similarity measures have limitations in taking the covariance among attributes into consideration and reflecting the effects of covariance in computation of distances among attributes. To deal with this challenging issue, this research examines the weighted Mahalanobis distance based similarity measure applied to CBR cost estimation and carries out the comparative study on the existing distance measurement methods of CBR. To validate the suggest CBR cost model, leave-one-out cross validation (LOOCV) using two different sets of simulation data are carried out. Consequently, this research is expected to provide an analysis of covariance effects in similarity measurement and a basis for further research on the fundamentals of case retrieval.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.449-451
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• 2003

The estimation of time-series data is fundamental process in many data analysis cases. However, the unwanted measurement error is usually added to true data, so that the exact estimation depends on efficient method to eliminate the error components. The wavelet transform method nowadays is expected to improve the accuracy of estimation, because it is able to decompose and analyze the data in various resolutions. Therefore, the wavelet based Kalman filter method for the estimation of time-series data is proposed in this paper. The wavelet transform separates the data in accordance with frequency bandwidth, and the detail wavelet coefficient reflects the stochastic process of error components. This property makes it possible to obtain the covariance of measurement error. We attempt the estimation of true data through recursive Kalman filtering algorithm with the obtained covariance value. The procedure is verified with the fundamental example of Brownian walk process.