• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.05a
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• pp.991-996
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• 2004

The international competition in refrigerator markets has continuously required the research for sound quality of a refrigerator to improve the quality of a life. In this paper, A new method for evaluation of the sound quality of a refrigerator is developed based on human sensibility engineering by using ANN(Artificial neural network). Finally it is applied to evaluate the sound qualify of refrigerator on the production line.

• 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.

• 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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• 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

• The Journal of the Acoustical Society of Korea
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• v.29 no.4
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• pp.258-264
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• 2010

In this paper, we propose an objective quality feature which is based on the human auditory system to measure vacuum cleaner noise. It is observed that some frequency bands are more sensitive to the human auditory system. Therefore, we divided the audible frequency range of vacuum cleaner noise into a number of frequency bands and the average energy of these bands was calculated. Among a number of average energies, an average energy of a frequency band was selected as the proposed feature. In order to test the performance of the proposed feature, fourteen vacuum cleaners were chosen and the noise was recorded in an anechoic-chamber. Then we performed subjective tests to obtain subjective scores of the noise data using the PCM (paired comparison method) and ACR (absolute category rating) subjective methods. The proposed objective quality feature shows high correlation with the subjective scores.

• 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.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.11a
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• pp.112-120
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• 2008

Today, the use of a vacuum cleaner gave us the higher quality of life than past time, but sometimes made us w1comfortable in the house because of the specific noise that is annoying. So we need to study how sound absorbtion materials affect sound power level and sound quality with sound metrics. In this paper, we will measure and calculate sound power level for vacuum cleaner and analyze characteristics of the noise for 10 Signals according to materials positioned in vacuum cleaner. The multiple regression analysis can estimate the nonlinear characteristics of relation between subjective evaluation and sound metrics. So we will develop sound quality index for vacuum sound.

• 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.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.11
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• pp.1195-1202
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• 2004

The international competition in refrigerator markets has continuously required the research for sound quality of a refrigerator to improve the quality of a life. In this paper, A new method for evaluation of the sound quality of a refrigerator is developed based on human sensibility engineering by using ANN(artificial neural network). In this paper, the loudness and the sharpness of the refrigerator's signals was used for the input value in ANN's training process because the loudness and the sharpness has a good correlation between the output of the ANN and the target of the individual evaluation In the training process. Two input factor was used repeatedly in the training process to get more optimum weighting value. And then finally we developed the sound quality index of a refrigerator. The developed sound quality index was confirmed by the 96.5 % of correlation between the output of the ANN and the real evaluation. It will be applied to evaluate the sound quality of a refrigerator in the industry.

• 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.