• 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.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.5 s.110
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• pp.457-469
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• 2006

In automotive engineering, the brand sound is one of the important advantage strategies 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 this paper, booming and rumbling sound, which are professional words used by sound and vibration engineers are used for the design of brand sound. We employed sound quality metrics, which are used in the psychoacoustics. By most research results, the relationship between subjective evaluations and sound quality metrics has nonlinear characteristics. In order to correlate these subjective evaluations with sound quality metrics, the artificial neural network technology has been applied to two-dimensional sound quality index for a passenger car. These indexes are used for 46 passenger cars, which are samples of the famous cars around the world. Also a preference evaluation for car sound was carried out by sound and vibration engineers. We coupled this preference with booming and rumbling sounds by using artificial neural network. In future, the two dimensional sound and preference index will be very useful to develop brand sound in passenger cars.

• Journal of ILASS-Korea
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• v.19 no.4
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• pp.204-210
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• 2014

Experimental study was conducted to investigate the effect of EGR(exhaust gas recirculation) on engine noise using single cylinder combustion ignition engine. Under constant engine rotary speed of 1200 RPM, 8 mg fuel quantity was injected with 15, 18 and 21% of oxygen ratio and 1400 bar of injection pressure. Using the in-cylinder pressure data acquired by a piezoelectric transducer, the engine performance parameters were calculated. Radiated engine noise measured for 10 seconds was analyzed using spectral characteristics and sound quality metrics such as loudness, sharpness, roughness. From the obtained engine performance parameters and sound quality metrics, effect of oxygen ratio of the premixed air, start of injection timing on frequency characteristic and sound quality metrics were analyzed. Correlation analysis was conducted between MPRR(maximum pressure rise rate), RI(ringing intensity) and sound quality metrics. RI was identified as the most important factor having influence on the sound quality metrics.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.785-790
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• 2014

The purpose of this study is to identify the significant sound quality metric and compose the sound quality index of motor driven roller blind which is part of vehicle sunroof. Before subjective evaluation, sound characteristics of roller blind was analyzed and set the target operating sound for subjective evaluation. Thus, transfer sound of roller blind which has the characteristics of sound modulation was used for subjective evaluation. Linear regression was carried out by chosen Zwicker's metrics which are pointed by comments of jurors. Loudness and sharpness related metrics are prime metrics in sound quality index we composed. Effect of roller blind assay when it is attached to real vehicle was identified to evaluate the validity of index.

• 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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• 2004.05a
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• pp.1003-1008
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• 2004

In our life, we have used many digital appliances. They helped us to improve the quality of lift but sometimes gave us unsatisfactory result because they produce specific noise. Especially a vacuum cleaner produces a great deal of noise that is very annoying. So we need to study what sound metrics affect human sensibility. In this paper, we will study sound quality index for vacuum cleaner. The subjective evaluation of vacuum cleaner sound can be indicated to objective parameters by sound metrics of psychoacoustics. The artificial neural network can estimate the nonlinear characteristics of relation between subjective evaluation and sound metrics. We applied the artificial neural network to the development of sound quality index for vacuum sound.

• The Journal of the Acoustical Society of Korea
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• v.25 no.3
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• pp.129-136
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• 2006

For the environmental noise assessments. A weighted equivalent noise level (LeqA) is used to measure the time varying environmental noise. However, it is not appropriately reflect various environmental noise features and human emotions. The human perception of the noise is affected largely by the psychoacoustic characteristics of noise as well as the sound pressure level In this study, the effective factors of noise qualify are analyzed using the subjective assessment and statistical analysis of environmental noise, such as road traffic noise. construction site noise, noise in daily living. and other. The analysis methodology is composed to three steps as follows : firstly, the values of the sound qualify metrics of various noise sources were analyzed. And to classify the noise sources, we conducted a cluster analysis using sound quality metrics. Secondly, subjective jury testing was carried out using the methods of paired comparisons and semantic differential. Finally, the correlation between the subjective parameters and the noise quality metrics were analyzed. As a result. the human perception characteristics of the various environmental noise are described in some physical parameters of the noise qualify metrics.

• 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.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.5
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• pp.427-436
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• 2010

The printer sound has many aspects which define its quality because the printer has lots of components and its operation is very complicated. These sound qualities are related to the international competition in printer markets. Recordings inside anechoic chamber were analyzed and a large number of sounds were stimulated using digital signal processing technique. First subjective tests of the printer sound were conducted using semantic different method. By applying factor analysis to the subjective response, two important factors of sound quality were extracted. Second subjective tests were conducted to evaluate the quietness and the impulsiveness of the printer sounds. On the other hand, sound metrics are calculated applying psychoacoustic theories. In this paper, the nonlinear relation between subjective evaluation and sound metrics was identified using artificial neural network and the printer sound quality index was developed. Later, subjective sound quality evaluation will be estimated and evaluated using this index.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.7 s.100
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• pp.821-828
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• 2005

In our life, we have used many digital appliances. They help us to improve the quality of life but sometimes give us unsatisfactory result. Because they produce specific noise. Especially vacuum cleaner produce much noise that is very annoying. So we need to study what sound metrics affect human sensibility. In this paper, we develop sound quality index for vacuum cleaner using the sound quality metrics defined in psychoacoustics. First, we carry out the subjective evaluation of vacuum cleaner sound to verify what vacuum sound feels good to human. And then artificial neural network estimated the complexity and the nonlinear characteristics of the relations between subjective evaluation and sound metrics. Finally the ANN is trained repeatedly to have a good performance for sound qualify index of the vacuum cleaner. As a result, the sound quality index of vacuum cleaner has a correlation of $93.5\%$ between the subjective evaluation and ANN. So, there exist three factors that Is loudness, sharpness, roughness which affect the sound quality of vacuum cleaner.