• 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.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.4 s.121
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• pp.298-309
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• 2007

There are various sounds in the car as much as cars have many mechanical parts. These sounds make various psychological development. The international competition in car markets has continuously required the research about the sound quality of a car. The domestic car makers have also invested a lot of money for the research and development of sound quality. Car axle plays an important role in a vehicle and its NVH development is also important. By this time, NVH development of car axle is mainly based on the reduction of sound pressure level (dBA), which cannot gives, the satisfaction to the customers in view of the sound quality of a vehicle. Therefore, in this paper, a sound quality index evaluating the sound quality of axle noise based on human sensibility is developed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11b
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• pp.174-179
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• 2005

In automotive engineering, the brand sound is one of the important advantage strategy in a car company. For the design of brand sound, the selection of descriptive word for a car sound is one of major works in automotive sound quality research. In paper, booming sound and rumbling sound, which are professional words used by NVH engineers are used for the design of brand sound. We employed sound metrics which are the subjective parameter used in psychoacoustics. According to most research results, the relationship between subjective evaluations and sound metrics has nonlinear characteristics and is very complex. In order to link these subjective evaluations to sound metrics, the artificial neural network technology has been applied to two-dimensional sound quality index for a passenger car. These indexes is used for 46 passenger cars, which are samples of famous cars in the world. Also the preference in car sounds is evaluated by the trained NVH engineers. We coupled this preference with booming and rumbling sounds by using artificial neural network. In future, the two -dimensional sound index and preference index are very useful fur the development of brand sound in passenger cars.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.10a
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• pp.827-827
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• 2009

Complaints against high-speed train interior noise have been increasing as a number of high-speed train passenger grows bigger. It is very difficult to analyze characteristics of high-speed train interior noise using sound pressure level only. It is requested to consider how the public response change for each high-speed train interior noise. This study presents evaluation of the sound quality for interior noise of KTX-II using Zwicker parameters. Characteristic of loudness and sharpness is different between noise samples depending on operation condition. The noise sample that recorded when the high-speed train passed through tunnel section is more louder and sharper.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.377-382
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• 2003

In our previous study, we have developed sound quality index for steady rumbling sound of passenger car. In this paper, we will study sound quality index for transient rumbling noise. The subjective evaluation of rumbling sound can be indicated to objective parameters by sound metrics of psychoacoustics and principal rumble component. And artificial neural network can be estimated complexity and nonlinear characteristics of relation between subjective evaluation and sound metrics. We applied to sound metrics and artificial neural network to development of sound quality index for transient rumbling sound of passenger car.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.628-634
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• 2003

Rumbling sound is one of the most important interior sound of a passenger cu. 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 th[ ory has been applied to derivation of sound quality index fur rumbling sound of a passenger car.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.13 no.6
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• pp.445-451
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• 2003

Booming sound is one of the most important interior sound of a passenger car. The conventional booming noise research was focused on the reduction of the A-weighted sound pressure level. However A-weighted sound pressure level cannot give the whole story about the booming sound of a passenger car. In this paper, we employed sound metrics, which are the subjective parameters, 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 booming sound of a passenger car.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2010.05a
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• pp.146-147
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• 2010

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.04a
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• pp.397-398
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• 2011

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.654-660
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• 2006

There are various sounds in the car as much as cats have many mechanical parts. These sounds make various sound qualities. The international competition in car markets has continuously required the research about the sound quality of a car. The domestic carmakers have also invested a lot of money for the research and development of sound quality. Car axle plays an important role in a vehicle and its NVH development is also important. By this time, NVH development of car axle is mainly based on the reduction of sound pressure level(dBA), which cannot gives, the satisfaction to the customers in view of the sound quality of a vehicle. Therefore, in this project, a sound quality index evaluating the sound quality of axle noise based on human sensibility is developed and applied to the development of the sound quality of axle noise