• Journal of Electrical Engineering and Technology
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• v.3 no.4
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• pp.451-459
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• 2008

Accurate load modeling is essential for power system static and dynamic analysis. By the nature of the problem of parameter estimation for power system load modeling using actual measurements, multiple local optimal solutions may exist and local methods can be trapped in a local optimal solution giving possibly poor performance. In this paper, Trust-Tech, a novel methodology for global optimization, is applied to tackle the multiple local optimal solutions issue in measurement-based power system load modeling. Multiple sets of parameter values of a composite load model are obtained using Trust-Tech in a deterministic manner. Numerical studies indicate that Trust-Tech along with conventional local methods can be successfully applied to power system load model parameter estimation in measurement-based approaches.

• Journal of Korean Institute of Industrial Engineers
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• v.19 no.2
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• pp.35-41
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• 1993

Statistical calibration is a useful technique for achieving compatibility between two different measurement methods, and it usually consists of two steps : (1) estimation of the relationship between the standard and nonstandard measurements, and (2) prediction of future standard measurements using the estimated relationship and observed nonstandard measurements. A predictive multivariate errors-in-variables model is presented for the multivariate calibration problem in which the standard as well as the nonstandard measurements are subject to error. For the estimation of the relationship between the two measurements, the maximum likelihood (ML) estimation method is considered. It is shown that the direct and the inverse predictors for the future unknown standard measurement are the same under ML estimation. Based upon large-sample approximations, the mean square error of the predictor is derived.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.6 s.99
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• pp.738-748
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• 2005

The ship radiated noise level fluctuates by the difference of interference and reverberation according to measurement methods and environmental conditions. These phenomena cause error of the source level estimation even in the same environment conditions. This paper describes a quantitative analysis and a reduction method for an error value to the source level estimation in spatial and temporal interference environment. The design criteria of the radiated noise measurement array composed of omni-directional hydrophones and the source level accuracy in the deep water range are given. The source level accuracy in the shallow water range is also derived based on the statistical model of the multiple reflection paths. The results are verified using the water tank experiment and the sea trial.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.153-156
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• 1996

A new filtering algorithm for radar tracking is developed based on the fact that correct evaluation of the measurement error covariance can be made possible by doing it with respect to the Cartesian state vector. The new filter may be viewed as a modification of the extended Kalman filter where the variance of the range measurement errors is evaluated in an adaptive manner. The structure of the proposed filter allows sequential measurement processing scheme to be incorporated into the scheme, and this makes the resulting algorithm favorable in both estimation accuracy and computational efficiency.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.2
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• pp.114-120
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• 2000

Fossil power plant availability is significantly affected by gradual degradations of equipment as operation of the plant continues. It is quite important to determine whether or not to replace some equipment and when to replace the equipment. Performance calculation and analysis can provide the information. Robustness in the performance calculation can be increased by using verification ＆ validation of measured input data. We suggest new algorithm in which estimation relation for validated measurement can be obtained using correlation between measurements. Input estimation model is obtained using design data and acceptance measurement data of domestic 16 fossil power plant. The model consists of finding mostly correlated state variable in plant state and mapping relation based on the model and current state of power plant.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.9
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• pp.101-108
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• 2007

State estimators are used to monitor the operating states of power systems in modern EMS. It iteratively calculates the voltage profile of the currently operating power system with voltage, current, and power measurements gathered from the entire system. All the measurements are usually assumed to be obtained simultaneously. It is practically impossible, however, to maintain the synchronism of the measurement data. Recently, phasor measurements synchronized via satellite are used for the operation of these power systems. This paper describes the modified state estimator used to support the processing of synchronized phasor measurements. Synchronized phasor measurements are found to provide synchronism of measurement data and improve the accuracy/redundancy of the measurement data for state estimation. The details of the developed state estimation program and some numerical results of operation are presented.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.1
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• pp.109-117
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• 2005

Range and velocity measurement algorithm is a procedure for estimating the accurate target position by using matched filter outputs equally spaced both in range and doppler frequency domain. Especially, in measurement algorithm for multi-function radar, it is necessary to consider processing time as well as accuracy in order to track multi-targets simultaneously. In this paper, we analyze range and velocity measurement algorithm using discriminator estimation method which is a technique applied to angle measurement of monopulse radar. The applied method required constant processing time for estimation can be used in multiple target tacking. But, it is necessary to consider measurement accuracy because of using minimum channel outputs for estimation. In the simulation, we show that the applied method is superior to the traditional gravity center measurement algorithm with respect to the accuracy performance and also analyze the characteristics of the proposed technique by calculating RMS error level as the processing parameters such as pulse width , channel step, etc. change.

• Journal of Electrical Engineering and Technology
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• v.4 no.2
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• pp.149-158
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• 2009

It is important to derive reliable parameter values in the measurement-based load model development of electric power systems. However parameter estimation tasks, in practice, often face the parameter identifiability issue; whether or not the model parameters can be estimated with a given input-output data set in reliable manner. This paper introduces concepts and practical definitions of the local identifiability of model parameters. A posteriori local identifiability is defined in the sense of nonlinear least squares. As numerical examples, local identifiability of third-order induction motor (IM) model and a Z-induction motor (Z-IM) model is studied. It is shown that parameter ill-conditioning can significantly affect on reliable parameter estimation task. Numerical studies show that local identifiability can be quite sensitive to input data and a given local solution. Finally, several countermeasures are proposed to overcome ill-conditioning problem in measurement-based load modeling.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.52 no.11
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• pp.493-495
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• 2003

Accurate temperature measurement is a key factor to implement the rapid thermal processing(RTP). A temperature estimation method using acoustic wave has been proposed to overcome the inaccuracy and contamination problem of the previous methods. The proposed method, however, may suffer from the offset and low resolution problem since it is implemented in the time domain. This paper presents a temperature estimation method using the phase detection of acoustic wave. Based on the frequency domain approach, the proposed technique increases the resolution of the measured temperature and reduces the effect of noise. We investigate the performance of the proposed method via experiments.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.6
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• pp.1198-1206
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• 2011

In this paper, a sensor bias estimation method with pseudo measurement for asynchronous multisensor systems is proposed. The proposed bias estimation method separates the local filter which estimates the target state with biased measurements into two parts, one is bias part, the other is target state part. By using these two parts, the algorithm generates the pseudo bias measurement for estimating bias, and then eliminates bias of local track through bias compensation. Finally, the proposed algorithm is evaluated by comparing with the existing EXX method.