• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2003년도 추계학술대회논문집
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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.

• 한국소음진동공학회논문집
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• 제16권5호
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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.

• 한국분무공학회지
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• 제19권4호
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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.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2014년도 추계학술대회 논문집
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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.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2005년도 추계 학술대회논문집(수송기계편)
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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.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2004년도 춘계학술대회논문집
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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.

• 한국음향학회지
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• 제25권3호
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• pp.129-136
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• 2006

소음에 대한 인간의 심리적 인지는 소음의 여러 가지 물리적 요인에 의하여 영향을 받는다. 그러나 현재의 환경소음 평가는 A 가중치 등가 소음 수준을 기준으로 평가되고 있으며 인간의 다양한 감성적 요인을 반영하지 못하고 있다. 따라서 본 연구에서는 환경소음 평가를 위하여 환경소음원 43개에 대하여 주관평가와 통계적 분석방법을 사용하여 인간의 감성에 영향을 주는 음질인자 (Sound quality factor)를 분석하였다. 분석방법은 먼저 다양한 환경소음원에 대한 음질물리량 (Sound quality metrics)을 분석하여 음원을 분류하였으며 분류된 음원의 주된 음질 물리량을 고찰하였다. 그리고 쌍대비교법 (Paired comparisons method)과 어의분별척도법 (Semantic differential method)을 사용하여 주관 평가를 실시하고 음질의 요인을 분석하였으며 물리량과의 관계를 규명하였다. 마지막으로 요인에 대한 물리량의 기여도를 분석함으로써 환경소음의 감성적 인지에 대한 기초 물리량을 설정하였다.

• 한국소음진동공학회논문집
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• 제13권6호
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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.

• 한국소음진동공학회논문집
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• 제20권5호
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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.

• 한국소음진동공학회논문집
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• 제15권7호
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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.