Show simple item record

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


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record