• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.4C
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• pp.462-467
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• 2007

This paper proposes Minimum Distance Searching Algorithm (MDSA) which reduces the computational complexity (CC) of the ML, the kind of Spatial Multiplexing (SM) MIMO system. The MDSA searchs candidate symbols with a starting symbol, which is called reference bits. We used the linear receiver of MIMO techniques to find a starting symbol. The MDSA searchs the shortest path to a transmitted symbol using reference bits and Minimum Distance(MD) concept. The CC of MDSA is reduced to the 0.21% to the ML as the transmit antennas is 4 in 16QAM. The simulation result shows the BER of MDSA is nearly same to the BER of ML as the transmit antennas is 2 and the receive antennas is 3 in 16QAM and slightly degraded to the BER of ML as the transmit antennas is 4 and the receive antennas is 6 in QPSK.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.8 s.173
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• pp.143-150
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• 2005

To verify applicability of multi-dimensional spectral analysis (MDSA) fur noise source identification two different approaches which are frequency response and coherent function have been investigated. The coherence function approach appears able to separate the correlated system when the noise sources were coherent. In this study, we identify contribution of structure-borne-noise of vehicle HVAC system using MDSA method. Firstly, to identify the applicability of MDSA method, 4-inputs of vehicle HVAC system were the signals measured by accelerometers attached on the selected noise sources which were composed of blower, evaporator, heater and duct. While 1-output which was driver's position sound was the SPL signals measured by a remote microphone, when the blower motor was operating. We identify efficiency of systems modeled with four Inputs/single output through ordinary coherence function (OCF) and partial coherence function (PCF). As a result of experiment, the blower accounted for $62-88\%$ of the overall level of sound energy density. Also, according to the analysis of acoustic signal and vibration signals measurement, an investigation of the noise source identification in the vehicle HVAC is presented. With the sound intensity method, the major sources of the vehicle HVAC radiation are verified. Also the method of improving the noise reduction is proposed by attaching damping patch access to blower motor and noise reduction is verified.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.8
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• pp.741-746
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• 2007

In this study, transfer path identification and output estimation are simulated by multi-dimension spectral analysis method (MDSA). Multi -input/single-output system give expression the vehicle suspension which each inputs are correlated reciprocally. In case of correlating with inputs, the system needs separating the each input signal by MDSA. Main simulations are about finding effective input by coherent output spectrum and selecting optimal input's number by multiple coherence function. Also, by shielding transfer path of each input, transfer path characteristic is identified in terms of overall integrated contribution level.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.9 s.252
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• pp.1154-1159
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• 2006

In this paper, time-frequency analysis and multi-dimensional spectral analysis methods are applied to source identification and diagnostic of non-stationary sound vibration signals. By checking the coherences for concerned time, this simulation is very well coincident to expected results. The proposed method analyzes the signal instantaneously in both time and frequency domains. The MDSA (Multiple Dimensional Spectral Analysis) analyzes the signal in the plane of instantaneous time and instantaneous frequency at the same time. And it was verified by using the 1500cc passenger car which is accelerated from 70Hz to 95Hz in 4 seconds, the proposed method is effective in determining the vehicle diagnostic problems.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.999-1004
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• 2004

In this study, we identify contribution of structure-borne-noise of vehicle HVAC system using Multi-Dimensional spectral analysis (MDSA) method. Firstly, to identify the applicability of MDSA method, the case of HVAC system was modeled with four input / single output system. The four inputs which is given vibration data is composed of blower, evaporator, heater and duct. The single output is noise data from driver's seat. When the blower motor is operating, we analyze the contributions of four input / single output. As a result of experiment, we identify efficiency of systems modeled with four input / single output through ordinary coherence function (OCF) and multiple coherence function (MCF).

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.21 no.1
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• pp.81-88
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• 2011

The method is introduced for estimating the noise source contribution on the noise of PDP TV in a multiple-input system where the input sources may be coherent with each other. By the coherence function method, it is found that the biggest part of the noise source in the PDP TV noise is generated by the PCB boards which consume high power and produce high heat. This analysis is modeled as three-input/single-output system because the noise is generated by three main boards, X-board, Y-board, SMPS that are located close to each other. The coherence function method is proved to be useful tool for identifying of noise source. In this study, Transfer Path Analysis using MDSA is implemented to determine the quantitative noise contribution of each board for PDP TV with the rear case closed and with the rear case open. And the possibility of noise reduction is confirmed through the experimental method that isolates the most contributing board by adding sound-absorbing materials to it.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.75-81
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• 2006

Recently, customers interest about noise of household electric appliance is growing. so, designer of product must study to reduce noise of product. Specially, in case of household electric appliance such as washing machine, there was consumers' complaint about noise that is radiated under dehydrating condition. But, in the case of washing machine, identification of noise source is not easy when washing machine is under dehydrating condition. Because various noise source influence each other, it is difficult to find out pure contribution degree about output noise. Multi-Dimensional Spectral Analysis(MDSA) is method that can remove correlation between inputs each other and express pure contribution degree about output of single input. So in this study, we analyzed contribution of each noise source on transfer pass of noise that is radiated at dehydration of washing machine using MDSA.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.11
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• pp.1056-1063
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• 2007

Recently, there has been a growing consumer interest in the amount of noise produced by household electrical appliances. The designer of the product must identify the source of the noise, in order to reduce the noise. In the case of a household electric appliance such as the washing machine, there is consumer's complaint about the noise that is generated during the dehydrating condition. Because of several noise sources combined each other. It is difficult to identify the noise sources that contribute to the noise output. Multi-Dimensional Spectral Analysis (MDSA) is a method that can remove the correlation between different noise sources, and it expresses the key contributing factor as a unique output. This study utilized MDSA to analyze the contribution of each input in the noise output during the dehydrating condition.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.10 s.175
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• pp.80-89
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• 2005

In this paper, time-frequency analysis using wavelet packet transform and advanced-MDSA (Multiple Dimensional Spectral Analysis) which based on wavelet packet transform is applied fur fault source identification and diagnosis of early detection of fault non-stationary sound/vibration signals. This method is analyzing the signal in the plane of instantaneous time and instantaneous frequency. The results of ordinary coherence function, which obtained by wavelet packet analysis, showed the possibility of early fault detection by analysis at the instantaneous time. So, by checking the coherence function trend, it is possible to detect which signal contains the major fault signal and to know how much the system is damaged. Finally, It is impossible to monitor the system is damaged or undamaged by using conventional method, because crest factor is almost constant under the range of magnitude of fault signal as its approach to normal signal. However instantaneous coherence function showed that a little change of fault signal is possible to monitor the system condition. And it is possible to predict the maintenance time by condition based maintenance for any stationary or non-stationary signals.

• Transactions of the Korean Society of Mechanical Engineers
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• v.10 no.4
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• pp.442-449
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• 1986

본 연구에서는 소음원 및 진동원을 규명하기 위하여 사용되어 온 종래의 주파 수응답함수(Frequency Response Function`FRF)법과 소음원 및 진동원 간에 강한 상관 관계가 존재한 경우에 사용되는 기여도함수(coherence function)법을 이용한 다차원 스텍트럼해석(Multi-Dimensional Spectral Analysis`MDSA)법에 의하여 가속도응답 및 방사음과의 기여관계를 규명하였다.