• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.339-340
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• 2010

• Journal of Electrical Engineering and Technology
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• v.6 no.4
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• pp.459-465
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• 2011

A phasor estimation algorithm based on the least square curve fitting technique for the distorted secondary current due to current transformer (CT) saturation is proposed. The mathematical form of the secondary current during CT saturation is represented as the scaled primary current with magnetizing current. The information on the scaled primary current is estimated using the least square technique, with the measured secondary current in the saturated section. The proposed method can estimate the phasor of a fundamental frequency component during the saturated period. The performance of the algorithm is validated under various fault and CT conditions using a C400 CT model. A series of performance evaluations shows that the proposed phasor estimation algorithm can estimate the phasor of the fundamental frequency component with high accuracy, regardless of fault conditions and CT characteristics.

• The Journal of Asian Finance, Economics and Business
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• v.5 no.1
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• pp.11-16
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• 2018

This research examines the alternative ways of estimating the coefficient of non-diversifiable risk, namely beta coefficient, in Capital Asset Pricing Model (CAPM) introduced by Sharpe (1964) that is an essential element of assessing the value of diverse assets. The non-parametric methods used in this research are the robust Least Trimmed Square (LTS) and Maximum likelihood type of M-estimator (MM-estimator). The Jackknife, the resampling technique, is also employed to validate the results. According to finance literature and common practices, these coecients have often been estimated using Ordinary Least Square (LS) regression method and monthly return data set. The empirical results of this research pointed out that the robust Least Trimmed Square (LTS) and Maximum likelihood type of M-estimator (MM-estimator) performed much better than Ordinary Least Square (LS) in terms of eciency for large-cap stocks trading actively in the United States markets. Interestingly, the empirical results also showed that daily return data would give more accurate estimation than monthly return data in both Ordinary Least Square (LS) and robust Least Trimmed Square (LTS) and Maximum likelihood type of M-estimator (MM-estimator) regressions.

• Tunnel and Underground Space
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• v.15 no.2 s.55
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• pp.137-144
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• 2005

An estimation technique of the joint diameter distribution using the least square method is suggested. When utilizing the technique by Song and Lee, the diameter distribution would be obtained only from the trace length distribution defined in an infinite window after the trace length distribution is estimated from the contained trace length distribution. With the new technique, however, the diameter distribution can be directly obtained from the sample histogram of the contained trace lengths. Compared with the previous technique, it shows a more accurate result for small sizes of joint samples and provides the joint geometry parameter of volumetric frequency. Verification of this new technique was completed by using Monte Carlo simulations.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.4
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• pp.645-650
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• 2007

This paper proposes a parameter estimation technique of a power transformer. Based on the combined equation, it estimates separately the primary and secondary leakage inductances using the least square method from the instantaneous voltages and currents in the steady state. The performance of the proposed technique was investigated by varying the cut-off frequency of the filter and the number of samples per cycle. The estimated values are obtained based on the average value for 41 cycle.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.3
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• pp.843-849
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• 1996

The least square estimation is used frequently in experimental modal analysis techinque to eliminate noise signals. However, identified modal parameters are sometimes inaccurate, since the least squre estimation is sensitive to noise. In this paper, a new total least squre estimation, which is robust to noise signals, is developed and applied to experimental modal analysis technique such as Prony method and Circle Fit method. Several simulated results show that the proposed method is robuster to noise than conventional method.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.2
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• pp.74-82
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• 2004

In this paper, a disturbance feedforward compensator design technique is proposed for an active magnetic bearing system subject to base motion for attenuating disturbance responses. In the consideration of the requirements on the model accuracy in the model based compensator designs, an experimental feedforward compensator design based on adaptive estimation by means of the Multiple Filtered-x least mean square(MFXLMS) algorithm is proposed. The performance and the effectiveness of the proposed technique will be presented in the succeeding paper in which the proposed technique is applied to a 2-DOF active magnetic bearing system subject to base motion.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.3
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• pp.51-55
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• 2006

An adaptive tracking controller is presented for the vibration reduction of flexible manipulator employed in hazardous area by combining input shaping technique with sliding-mode control. The combined approach appears to be robust in the presence of severe disturbance and unknown parameter which will be estimated by least-square method in real time. In a maneuver strategy, it is found that a hybrid trajectory with a combination of low frequency mode and rigid-body mode results in better performance and is more efficient than the traditional rigid body trajectory alone which many researchers have employed. The feasibility of the adaptive tracking control approach is demonstrated by applying it to the simplified model of robot system. For the applications of the proposed technique to realistic systems, several requirements are discussed such as control stability and large system order resulted from finite element modeling.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.42-43
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• 2007

This paper proposes a parameter estimation technique of a power transformer. Based on the combined equation, it estimates separately the primary and secondary leakage inductances, winding resistances using the least square method from the instantaneous voltages and currents in the steady state. The performance of the proposed technique was investigated by varying the cut-off frequency of the filter and the number of samples per cycle. The technique estimates the parameters with higher sampling frequencies.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.886-890
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• 2007

Machine fault prognosis techniques have been considered profoundly in the recent time due to their profit for reducing unexpected faults or unscheduled maintenance. With those techniques, the working conditions of components, the trending of fault propagation, and the time-to-failure are forecasted precisely before they reach the failure thresholds. In this work, we propose an approach of Least Square Regression Tree (LSRT), which is an extension of the Classification and Regression Tree (CART), in association with one-step-ahead prediction of time-series forecasting technique to predict the future conditions of machines. In this technique, the number of available observations is firstly determined by using Cao's method and LSRT is employed as prognosis system in the next step. The proposed approach is evaluated by real data of low methane compressor. Furthermore, the comparison between the predicted results of CART and LSRT are carried out to prove the accuracy. The predicted results show that LSRT offers a potential for machine condition prognosis.