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    A Study on the Sound Quality Evaluation Model of Mechanical Air-Cleaners

    Source: Journal of Vibration and Acoustics:;2009:;volume( 131 ):;issue: 003::page 34502
    Author:
    Jeong-Guon Ih
    ,
    Youn-Young Jeung
    ,
    Su-Won Jang
    ,
    Cheol-Ho Jeong
    DOI: 10.1115/1.3085889
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: In operating the air-cleaner for a long time, people in a quiet enclosed space expect low sound at low operational levels for a routine cleaning of air. However, in the condition of high operational levels of the cleaner, a powerful yet nonannoying sound is desired, which is connected to a feeling of an immediate cleaning of pollutants. In this context, it is important to evaluate and design the air-cleaner noise to satisfy such contradictory expectations from the customers. In this study, a model for evaluating the sound quality of air-cleaners of mechanical type was developed based on objective and subjective analyses. Sound signals from various air-cleaners were recorded and they were edited by increasing or decreasing the loudness at three wide specific-loudness bands: 20–400 Hz (0–3.8 barks), 400–1250 Hz (3.8–10 barks), and 1.25–12.5 kHz bands (10–22.8 barks). Subjective tests using the edited sounds were conducted by the semantic differential method (SDM) and the method of successive intervals (MSI). SDM tests for seven adjective pairs were conducted to find the relation between subjective feeling and frequency bands. Two major feelings, performance and annoyance, were factored out from the principal component analysis. We found that the performance feeling was related to both low and high frequency bands, whereas the annoyance feeling was related to high frequency bands. MSI tests using the seven scales were conducted to derive the sound quality index to express the severity of each perceptive descriptor. Annoyance and performance indices of air-cleaners were modeled from the subjective responses of the juries and the measured sound quality metrics: loudness, sharpness, roughness, and fluctuation strength. The multiple regression method was employed to generate sound quality evaluation models. Using the developed indices, sound quality of the measured data was evaluated and compared with the subjective data. The difference between predicted and tested scores was less than 0.5 points.
    keyword(s): Noise (Sound) , Sound , Sound quality , Electromagnetic spectrum , Surface roughness , Design AND Principal component analysis ,
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      A Study on the Sound Quality Evaluation Model of Mechanical Air-Cleaners

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    contributor authorJeong-Guon Ih
    contributor authorYoun-Young Jeung
    contributor authorSu-Won Jang
    contributor authorCheol-Ho Jeong
    date accessioned2017-05-09T00:36:00Z
    date available2017-05-09T00:36:00Z
    date copyrightJune, 2009
    date issued2009
    identifier issn1048-9002
    identifier otherJVACEK-28900#034502_1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/142288
    description abstractIn operating the air-cleaner for a long time, people in a quiet enclosed space expect low sound at low operational levels for a routine cleaning of air. However, in the condition of high operational levels of the cleaner, a powerful yet nonannoying sound is desired, which is connected to a feeling of an immediate cleaning of pollutants. In this context, it is important to evaluate and design the air-cleaner noise to satisfy such contradictory expectations from the customers. In this study, a model for evaluating the sound quality of air-cleaners of mechanical type was developed based on objective and subjective analyses. Sound signals from various air-cleaners were recorded and they were edited by increasing or decreasing the loudness at three wide specific-loudness bands: 20–400 Hz (0–3.8 barks), 400–1250 Hz (3.8–10 barks), and 1.25–12.5 kHz bands (10–22.8 barks). Subjective tests using the edited sounds were conducted by the semantic differential method (SDM) and the method of successive intervals (MSI). SDM tests for seven adjective pairs were conducted to find the relation between subjective feeling and frequency bands. Two major feelings, performance and annoyance, were factored out from the principal component analysis. We found that the performance feeling was related to both low and high frequency bands, whereas the annoyance feeling was related to high frequency bands. MSI tests using the seven scales were conducted to derive the sound quality index to express the severity of each perceptive descriptor. Annoyance and performance indices of air-cleaners were modeled from the subjective responses of the juries and the measured sound quality metrics: loudness, sharpness, roughness, and fluctuation strength. The multiple regression method was employed to generate sound quality evaluation models. Using the developed indices, sound quality of the measured data was evaluated and compared with the subjective data. The difference between predicted and tested scores was less than 0.5 points.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleA Study on the Sound Quality Evaluation Model of Mechanical Air-Cleaners
    typeJournal Paper
    journal volume131
    journal issue3
    journal titleJournal of Vibration and Acoustics
    identifier doi10.1115/1.3085889
    journal fristpage34502
    identifier eissn1528-8927
    keywordsNoise (Sound)
    keywordsSound
    keywordsSound quality
    keywordsElectromagnetic spectrum
    keywordsSurface roughness
    keywordsDesign AND Principal component analysis
    treeJournal of Vibration and Acoustics:;2009:;volume( 131 ):;issue: 003
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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