• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.311-317
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• 2007

The reduction of the Vehicle interior noise has been the main interest of NVH engineers. The driver's perception on the vehicle noise is affected largely by psychoacoustic characteristic of the noise as well as the SPL. The previous methods to evaluation of the SQ about vehicle interior noise are linear regression analysis of subjective SQ metrics by statistics and the estimation of the subjective SQ values by neural network. But these are so depended on jury test very much that they result in many difficulties. So, to reduce jury test weight, we suggested a new method using Mahalanobis distance for SQ evaluation. And, optimal characteristic values influenced on the result of the SQ evaluation were derived by signal to noise ratio(SN ratio) of the Taguchi method. Finally, the new method to evaluate SQ is constructed using Mahalanobis-Taguchi system(MTS). Furthermore, the MTS method for SQ evaluation was compared by the result of SQ grade table at the previous study and their virtues and faults introduced.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.4
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• pp.315-323
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• 2013

Tire noise is divided into a road noise(structure-borne noise) and a pattern noise(air-borne noise). Whilst the road noise is caused by the structural vibration of the components on the transfer path from tire to car body, the pattern noise is generated by the air-pumping between tire and road. In this paper, a practical method to estimate the pattern noise inside a passenger car is proposed. The method is developed based on the sound intensity and airborne source quantification. Sound intensity is used for identifying the noise sources of tire. Airborne source quantification is used for estimating the sound pressure level generated by each noise source of a tire. In order to apply the airborne source quantification to the estimation of the sound pressure, the volume velocity of each source should be obtained. It is obtained by using metrics inverse method. The proposed method is successfully applied to the evaluation of the interior noises generated by four types of tires with different pattern each other.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.4
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• pp.393-399
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• 2008

The reduction of the Vehicle interior noise has been the main interest of NVH engineers. The driver's perception on the vehicle noise is affected largely by psychoacoustic characteristic of the noise as well as the SPL. The previous methods to evaluation of the SQ about vehicle interior noise are linear regression analysis of subjective SQ metrics by statistics and the estimation of the subjective SQ values by neural network. But these are so depended on jury test very much that they result in many difficulties. So, to reduce jury test weight, we suggested a new method using Mahalanobis distance for SQ evaluation. And, optimal characteristic values influenced on the result of the SQ evaluation were derived by signal to noise ratio(SN ratio) of the Taguchi method. Finally, the new method to evaluate SQ is constructed using Mahalanobis-Taguchi system(MTS). Furthermore, the MTS method for SQ evaluation was compared by the result of SQ grade table at the previous study and their virtues and faults introduced.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.6 s.249
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• pp.728-733
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• 2006

The reduction of the Vehicle interior noise has been the main interest of NVH engineers. The driver's perception on the vehicle noise is affected largely by psychoacoustic characteristic of the noise as well as the SPL. In particular, the HVAC sound among the vehicle interior noise has been reflected sensitively in the side of psychology. In previous study, we have developed to verify identification of source for the vehicle HVAC system through multiple-dimensional spectral analysis. Also we carried out objective assessments on the vehicle HVAC noises and subjective assessments have been already performed with 30 subjects. In this study, the linear regression models were obtained for the subjective evaluation and the sound quality metrics. The regression procedure also allows you to produce diagnostic statistics to evaluate the regression estimates including appropriation and accuracy. Appropriation of regression model is necessary to $R^2$ value and F-value. And testing for regression model is necessary to independence, homoscedesticity and normality. Also we selected optimum layout of damping material using Taguchi method. As a result of application, sound quality is improved more quietly, powerfully, even though costly, and smoothly.

• The Journal of the Acoustical Society of Korea
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• v.37 no.3
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• pp.147-155
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• 2018

In this paper, we tried to find out sound quality metrics to express discomfort of overload excavator noise and to develop sound quality indexes through multiple regression analysis by using them. For this purpose, the interior noise of cabin under overload condition was recorded for six excavator models with different noise properties and Jury test was carried out by PCM (Paired Comparison Method) and MEM (Magnitude Estimation Method). Jury test result with low consistency was classified into two groups with different preference tendencies by cluster analysis and multiple regression analysis was conducted in order to find out which sound quality metrics have significant effects on discomfort(low preference). As a result, we figured out that the sound quality metrics to express the discomfort were the partial loudness (= $PN_{10Bark}$) between 0 and 10 Bark in case of group1 and the difference between engine noise(= $dB_{EG}$) and hydraulic system noise ($dB_1$) in case of group2. Using the results of preference ranking and tendency analysis of PCM followed by the correlation analysis between PCM and MEM, the more reliable results were adopted by excluding the data with low consistency obtained from Jury test via MEM.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.12
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• pp.1871-1876
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• 2010

The reduction of vehicle interior noise has been the main interest of NVH engineers. The driver's perception of the vehicle noise is strongly affected by the psychoacoustic characteristics of the noise and the SPL. The existing methods to evaluate the SQ for vehicle interior noise are linear regression analysis of subjective SQ metrics by statistics and the estimation of subjective SQ values by neural network. However, these methods strongly depend on jury tests, this leads to difficulties. To reduce the important of the jury tests, we suggest a new method using the Mahalanobis distance for SQ evaluation. And, the optimal characteristic values that influenced the results of sound quality evaluation on the basis by main effect. Finally, we developed a new method based on the MD method to evaluate sound quality. The result of noise evaluation revealed that the sound quality could be well improved by changing the structural characteristics of the vehicle.

• Bulletin of the Korean Mathematical Society
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• v.40 no.2
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• pp.319-326
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• 2003

In this paper, we obtain the optimal condition of the curvature bounds guaranteeing that Euclidean cones over Aleksandrov spaces of curvature bounded above preserve the curvature bounds, by considering the Euclidean cone CS$_{r}$ $^{n}$ over n-dimensional sphere S$_{r}$ $^{n}$ of radius r. More precisely, we show that for r<1, the Euclidean cone CS$_{r}$ $^{n}$ of S$_{r}$ $^{n}$ is a CBB(0) space, but not a CBA($textsc{k}$)-space for any real $textsc{k}$$\in$R.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.05a
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• pp.997-1002
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• 2004

Rumbling sound is one of the most important interior sound of a passenger car. The conventional rumbling noise research was focused on the reduction of the A-weighted sound pressure level. However A-weighted sound pressure level can not give the whole story about the rumbling sound of a passenger car. In this paper, we employed sound metric which is the subjective parameter used in psycoacoustics. According to recent research results, the relation between sound metrics and subjective evaluation is very complex and has nonlinear characteristics. In order to estimate this nonlinear relationship, artificial neural network theory has been applied to derivation of sound quality index for rumbling sound of a passenger car.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.04a
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• pp.447-452
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• 2012

Among the various elements affecting a customer's evaluation of automobile quality, buzz, squeak and rattle (BSR) are considered to be major factors. In most vehicle manufacturers, the BSR problems are solved by find-fix method with the vehicle road test, mainly due to various excitation sources, complex generation mechanism and subjective response. The aim of this paper is to develop the integrated experimental method to systematically tackle the BSR problems in early stage of the vehicle development cycle by resolving these difficulties. To achieve this aim, the developed experimental method ought to include the following requirements: to find and fix the BSR problem for modules instead of a full vehicle in order to tackle the problem in the early stage of the vehicle development cycle; to develop the exciter system including the zig and road-input-signal reproducing algorithm; to automatically localize the source region of BSR; to develop sound quality index that can be used to assess the subjective responses to BSR. Also, the BSR sound quality indexes based on the Zwicker's sound quality parameters using a multiple regression analysis. The four sound metrics from Zwicker's sound quality parameter are computed for the signals recorded for eight BSR noise source regions localized by using the acoustic-field visualized results. Then, the jury test of BSR noise are performed for participants. On a basis of the computed sound metrics and jury test result, sound quality index is developed to represent the harsh of BSR noise. It is expected that the developed BSR detection system and sound quality indexes can be used to reduce the automotive interior BSR noise in terms of subjective levels as well as objective levels.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.25 no.3
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• pp.141-149
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• 2015

In this study, there is an investigation about the sound quality of automotive horn that attached to luxury sedans. In order to define a questionnaire of horn sound quality the factor analysis is conducted. Ten automotive horns are selected for this research and ten passenger cars(nine is luxury sedan and one economy class car). Luxury is used for the questionnaire as an attribute for the sound quality of car horn. The interior noises for ten test cars are recorded and used for the subjective analysis of car horn sound. In the paper, new sound metric for the car horn sound is presented. The new sound metric is used for the objective sound index for the prediction of subjective sound quality of car horn.