• Nuclear Engineering and Technology
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• v.49 no.7
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• pp.1555-1562
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• 2017

A loose part monitoring system is used to identify unexpected loose parts in a nuclear reactor vessel or steam generator. It is still necessary for the mass estimation of loose parts, one function of a loose part monitoring system, to develop a new method due to the high estimation error of conventional methods such as Hertz's impact theory and the frequency ratio method. The purpose of this study is to propose a mass estimation method using a Markov decision process and compare its performance with a method using an artificial neural network model proposed in a previous study. First, how to extract feature vectors using discrete cosine transform was explained. Second, Markov chains were designed with codebooks obtained from the feature vector. A 1/8-scaled mockup of the reactor vessel for OPR1000 was employed, and all used signals were obtained by impacting its surface with several solid spherical masses. Next, the performance of mass estimation by the proposed Markov model was compared with that of the artificial neural network model. Finally, it was investigated that the proposed Markov model had matching error below 20% in mass estimation. That was a similar performance to the method using an artificial neural network model and considerably improved in comparison with the conventional methods.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.8
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• pp.823-831
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• 2008

Since it needs the light computational load and small database, sound source localization method using time delay of arrival(TDOA method) is applied at many research fields such as a robot auditory system, teleconferencing and so on. Researches for time delay estimation, which is the most important thing of TDOA method, had been studied broadly. However studies about factors for time delay estimation are insufficient, especially in case of real environment application. In 1997, Brandstein and Silverman announced that performance of time delay estimation deteriorates as reverberant time of room increases. Even though reverberant time of room is same, performance of estimation is different as the specific part of signals. In order to know that reason, we studied and analyzed the factors for time delay estimation using speech signal and room impulse response. In result, we can know that performance of time delay estimation is changed by different R/D ratio and signal characteristics in spite of same reverberant time. Also, we define the performance index(PI) to show a similar tendency to R/D ratio, and propose the method to improve the performance of time delay estimation with PI.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.10
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• pp.2038-2040
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• 2009

This paper studies the state estimation problem for the current of DC/DC boost converters with parasitic inductor resistance. The parasitic resistance increases the system uncertainty when the output load variation occurs. In order to enhance the observation performance of the Luenberger observer this paper includes the integral of the estimation error signal to the estimation algorithm. By using the proposed PI observer the converter current signal is successfully reconstructed with the voltage measurement regardless of the load uncertainty. Computer simulation has been carried out by using Simulink/Sim Power System. Simulation results show the proposed method maintains robust estimation performance against the model uncertainty.

• Proceedings of the KIPE Conference
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• 1998.10a
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• pp.149-152
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• 1998

From the viewpoint of model-based current control, it is indispensable to use the accurate system parameters for the high control performance. This paper adopts the Least-Squares algorithm as a parameter estimation scheme because it has the fast convergence rate and the low sensitivity to noises. In case of the intelligent current controller with delay compensator, the simulation results show that the adopted estimation scheme can be successfully applied to PWM converters and also show the improved control performance in the estimated parameters.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.04b
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• pp.278-282
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• 1995

We developed a part of storke sensing cylinder using magnetic sensor and estimated is performance. In this paper, for the performance estimation of stroke sensing cylinder. We consist of hydrallic system using solenoid valve with ON/OFF motion. In order to the control of solenoid valve for the position control of cylinder rod, PWM (Pulse Width Modulation) method which modulates time pulse width in proportion to error was used. A performance of cylinder rod with magnetic scales was evaluated by its hydraulic system.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.4
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• pp.36-45
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• 2014

Model based control methods are widely used to improve the control performance of diesel engine air systems because the control results of the air system significantly affect the emission level and drivability. However, the model based control algorithm requires a lot of unmeasurable states which are hard to be measured in a mass production engine. In this study, an air system model of the diesel engine is proposed to estimate 11 unmeasurable states using only sensors equipped in a mass production engine. In order to improve the estimation performance in the transient condition, dynamic characteristics of the air system are analyzed and implemented as discrete filters. Turbine and compressor efficiency models are also proposed to overcome a limitation of the constant or look-up table based efficiency values. The proposed air system model was validated in steady state and transient conditions by real-time engine experiments. The maximum error of the estimation for 11 physical states was 11.7%.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.12
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• pp.1449-1454
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• 2009

The performance variation of a multibody system is affected by a variation of various design variables of the system. And the effects of design variable variations on the performance variation must be considered in design of a multibody system. Accordingly, a variation analysis of a multibody system needs to be conducted in design of a multibody system. For a variation analysis of a performance, population mean and variance which are called statistical parameters of design variables are needed. However, an evaluation of statistical parameters of design variables is impossible in many practical cases. Therefore, an estimation of statistical parameters of the performance based on sample mean and variance which are called statistic of design variables is needed. In this paper, the variation analysis method for a multibody system based on design variable samples was proposed. And, using the proposed method, a variation analysis of the vehicle ride comfort based on sample statistic of design variables was conducted.

• Journal of Digital Convergence
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• v.12 no.3
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• pp.249-254
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• 2014

Wireless LAN system is evolving toward high-speed data transmission and more accurate channel estimation is necessarily required to improve communication performance. The PLCP preamble field in IEEE 802.11 based wireless MODEM consists of ten short symbols and two long symbols and is used for synchronization and channel estimation. The existing least square (LS) channel estimation is based on only two long training symbols. After estimating channel response separately by using each long training symbol, the final channel estimation is obtained by the average of each estimation. In this paper, a new channel estimation algorithm is presented to improve the performance of the existing LS channel estimation algorithm. From the fact that the short training symbol consists of 12 non-zero subcarriers, it gives us a clue of being able to additionally estimate at least one fourth of channel coefficients. The new LS algorithm performs channel estimation based on both two long training symbols and a short training symbol. The proposed LS algorithm shows a little bit performance improvement over the existing LS estimation and it will be able to be applied to the IEEE 802.11p WAVE system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.10
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• pp.1458-1464
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• 2013

This paper proposed a new real time catenary impedance estimation technique using synchronized power data from the measured data of operating vehicle and substation for catenary protective relay and fault locator setting. This paper presented estimation equation of catenary impedance using synchronized power data between substation and vehicle of AT feeding system for the performance verification of the proposed technique. Also AC feeding system is modeled through power analysis program and performance was verified through simulation according to various load changes. We verified that average 2.38%(distance equivalent 23.8 m) error appeared between the proposed estimation equation of catenary impedance and power analysis program simulation output in no connection double track system between up track and down track. Furthermore, We confirmed that estimation error is bigger depending on the increasing the distance from substation and vehicle impedance using only using vehicle current when calculating vehicle impedance in connection double track system between up track and down track. But, We confirmed that the proposed technique estimated accurately catenary impedance regardless of vehicle impedance and distance from substation.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.64-69
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• 1993

In this paper we present the performance bounds of the optimal FIR filter in continuous time systems with modeling uncertainty. The performance measure bounds are calculated from the estimation error covariance bounds of the optimal FIR filter and the suboptimal FIR filter. Performance error bounds range are expressed by the upper bounds on the estimation error covariance difference between the real and nominal values in case of the systems with noise uncertainty or model uncertainty. The performance bounds of the systems are derived on the assumption that the system uncertainty and the estimation error covariance are imperfectly known a priori. The estimation error bounds of the optimal FIR filter is compared with those of the Kalman filter via a numerical example applied to the estimation of the motion of an aircraft carrier at sea, which shows the former has better performances than the latter.