• The Journal of the Acoustical Society of Korea
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• v.5 no.1
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• pp.24-34
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• 1986

Recently, as the noise problems of mechancial structures have been more serious, much studies are being carried out on the identification of noise sources and the reduction of noise level. In this paper, as the application of frequency analysis, the multi-dimensional spectral analysis method is applied to daisy wheel printer to identify the noise sources, and the relationship between sound pressure and vibration of printer is found in narrow and overall frequency range. The results of this study are compared with those of frequency response function method, thus, the applicability of multidimensional spectral analysis method is verified. It can be found, in a overall frequency range, that the vibration of platen have the worst effect on noise level, and the noise level reduction of 6dB, 7.9dB is obtained by changing the platen thickness to 2mm, 4mm, respectively.

• Proceedings of the KSR Conference
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• 2009.05a
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• pp.1069-1077
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• 2009

For external noise prediction of railway vehicles, sophisticated individual source modelling as well as appropriate noise propagation model from the sources is necessary to ensure the accuracy of the predicted results and contributions of each equipment to the overall noise levels. Accurate and reasonable identification procedures of sound sources of equipment including source strength, directivity and positions installed in the train play an important role in a prediction model, since it is not easy to establish a simple model for the sources with a single rule due to the complexity of source characteristics of equipment in size and directivity pattern. This paper guidelines practical considerations for identification of noise sources in railway vehicles including typical source characteristics of several sub-systems that emits noise to the environment, particularly for electric multiple unit(EMU), and verify effectiveness of assumptions used in the modelling of equipment by measurement with a simple part. The predicted external noise level of a complete train using Exnoise, which was developed by Hyundai-Rotem and has been verified in the a lot of field-tests, incorporating source modelling considered in this paper shows close correlation with the measured ones.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.4
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• pp.328-335
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• 2017

In this paper, we propose an efficient method to remove noise component contained in high resolution range profile(HRRP) to improve target identification performance. The proposed method can effectively eliminate the noise component using both the statistical characteristics of the noise component and EMD algorithm. Experimental results show that the proposed method can substantially improve the identification capability, removing the noise component effectively.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2216-2218
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• 2002

A system identification is to measure the output in the presence of a adequate input for the controlled system and to estimate the mathematical model in the basic of input output data. In the system identification, it is possible to estimate the true parameter values by the adjusted least squares method in the input-output case of no observed noise, and it is possible to estimate the true parameter values by the total least squares method in the input-output case with the observed noise. In recent the adjusted least squares method is suggested as a consistent estimation method in the system identification not with the observed noise input but with the observed noise output. In this paper we have developed the adjusted least squares method from the least squares method and have made certain of the efficiency in comparing the estimating results with the generating data by the computer simulations.

• ETRI Journal
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• v.34 no.1
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• pp.130-133
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• 2012

Recently, several noise-robust adaptive multichannel LMS algorithms have been proposed based on the spectral flatness of the estimated channel coefficients in the presence of additive noise. In this work, we propose a general form for the algorithms that integrates the existing algorithms into a common framework. Computer simulation results are presented and demonstrate that a new proposed algorithm gives better performance compared to existing algorithms in noisy environments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.8
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• pp.1984-1989
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• 1998

Convergence properties of the stochastic gradient adaptive algorithm based on the least mean absolute third (LMAT) error criterion is presented.In particular, the performnce of the algorithmis examined and compared with least mena square (LMS) algorithm for several different probability densities of the measurement noisein a system identification mode. It is observedthat the LMAT algorithm outperforms the LMS algorithm for most of the noise probability densities, except for the case of the exponentially distributed noise.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.3
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• pp.144-151
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• 2002

This work focuses on finding out the noise source and the method of reducing the noise level of LPG(liquefied petroleum gas) fuel injector. The noise of LPG injector in operating condition is due to the impact between valve and valve seat. This study shows that if the revolution of engine is increased, the noise of LPG injector will be more serious but it is not nearly affected by the increment of fuel pressure. The source and transmission paths of noise are identified through the analysis of noise generation mechanism and noise spectrum. The sound absorbing material is tested to verify its efficiency of sound absorption thor the LPG injector. The effect of noise reduction of absorbing material is remarkable when the engine speed is high. Consequently two methods of reducing the noise level are suggested from the identified results. The one is to equip the absorbing material on the outer side of injector and the other is to coat with a soft material or equip a soft ring on the surface of impact.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.15 no.3
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• pp.202-212
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• 2005

This study was aimed at rating the existing work environment noise components and alternatives in point of worker's view. To answer the purpose, AHP(Analytic Hierarchy Process) method is adopted in this research. Based on the AHP method, this research abstracts a mathematically rigorous noise components and alternative's weights and proven process for priority and decision-making. By reconstructing complex hearing conservation programs to a series of pair-wise comparisons, and then synthesizing the results, this study not only helps establishments of noise countermeasure, but also provides a clear rationale for noise alternatives. The result of this study is summarized as follows; 1) Job satisfaction index and noise identification index are 63, 56 respectively. 2) Noise level(15.7%), frequency(14.1%) and directivity(13.6%) are main reasons in worker's ground. 3) There are some difference between the estimation of worker's identification and that of work sites. 4) Low noise machine(14.7%), enclosure(13.2%) and shielding(9.6%) are chosen for noise protection method by workers. 5) Noise environment improvement should be focused on noise source rather than personal protection. 6) By the AHP method, noise source countermeasure have a key role at work environments.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.12 s.117
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• pp.1192-1200
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• 2006

Viscoelastic damping materials are widely used to reduce noise and vibration because of its low cost and easy implementation, for examples, on the body structure of passenger cars, air planes, electric appliances and ships. To design the damped structures, the material property such as elastic modulus and loss factor is essential information. The four-parameter fractional derivative model well describes the dynamic characteristics of the viscoelastic damping materials with respect to both frequency and temperature. However, the identification procedure of the four-parameter is very time-consuming one. In this study a new identification procedure of the four-parameters is proposed by using an FE model and a gradient-based numerical search algorithm. The identification procedure goes two sequential steps to make measured frequency response functions(FRF) coincident with simulated FRFs: the first one is a peak alignment step and the second one is an amplitude adjustment step. A numerical example shows that the proposed method is useful in identifying the viscoelastic material parameters of fractional derivative model.

• Smart Structures and Systems
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• v.11 no.1
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• pp.19-34
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• 2013

The objective of this paper is to develop on-line system parameter estimation and damage detection technique from the response measurements through using the Recursive Covariance-Driven Stochastic Subspace identification (RSSI-COV) approach. To reduce the effect of noise on the results of identification, discussion on the pre-processing of data using recursive singular spectrum analysis (rSSA) is presented to remove the noise contaminant measurements so as to enhance the stability of data analysis. Through the application of rSSA-SSI-COV to the vibration measurement of bridge during scouring experiment, the ability of the proposed algorithm was proved to be robust to the noise perturbations and offers a very good online tracking capability. The accuracy and robustness offered by rSSA-SSI-COV provides a key to obtain the evidence of imminent bridge settlement and a very stable modal frequency tracking which makes it possible for early warning. The peak values of the identified $1^{st}$ mode shape slope ratio has shown to be a good indicator for damage location, meanwhile, the drastic movements of the peak of $2^{nd}$ mode slope ratio could be used as another feature to indicate imminent pier settlement.