Detailed Information

Cited 4 time in webofscience Cited 7 time in scopus
Metadata Downloads

Noise Localization Method for Model Tests in a Large Cavitation Tunnel Using a Hydrophone Array

Full metadata record
DC Field Value Language
dc.contributor.authorPark, Cheolsoo-
dc.contributor.authorKim, Gun-Do-
dc.contributor.authorPark, Young-Ha-
dc.contributor.authorLee, Keunhwa-
dc.contributor.authorSeong, Woojae-
dc.date.accessioned2021-08-03T04:42:04Z-
dc.date.available2021-08-03T04:42:04Z-
dc.date.issued2016-03-
dc.identifier.issn2072-4292-
dc.identifier.issn2072-4292-
dc.identifier.urihttps://www.kriso.re.kr/sciwatch/handle/2021.sw.kriso/674-
dc.description.abstractModel tests are performed in order to predict the noise level of a full ship and to control its noise signature. Localizing noise sources in the model test is therefore an important research subject along with measuring noise levels. In this paper, a noise localization method using a hydrophone array in a large cavitation tunnel is presented. The 45-channel hydrophone array was designed using a global optimization technique for noise measurement. A set of noise experiments was performed in the KRISO (Korea Research Institute of Ships & Ocean Engineering) large cavitation tunnel using scaled models, including a ship with a single propeller, a ship with twin propellers and an underwater vehicle. The incoherent broadband processors defined based on the Bartlett and the minimum variance (MV) processors were applied to the measured data. The results of data analysis and localization are presented in the paper. Finally, it is shown that the mechanical noise, as well as the propeller noise can be successfully localized using the proposed localization method.-
dc.language영어-
dc.language.isoENG-
dc.publisherMDPI-
dc.titleNoise Localization Method for Model Tests in a Large Cavitation Tunnel Using a Hydrophone Array-
dc.typeArticle-
dc.publisher.location스위스-
dc.identifier.doi10.3390/rs8030195-
dc.identifier.scopusid2-s2.0-84962483442-
dc.identifier.wosid000373627400101-
dc.identifier.bibliographicCitationREMOTE SENSING, v.8, no.3-
dc.citation.titleREMOTE SENSING-
dc.citation.volume8-
dc.citation.number3-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaEnvironmental Sciences & Ecology-
dc.relation.journalResearchAreaGeology-
dc.relation.journalResearchAreaRemote Sensing-
dc.relation.journalResearchAreaImaging Science & Photographic Technology-
dc.relation.journalWebOfScienceCategoryEnvironmental Sciences-
dc.relation.journalWebOfScienceCategoryGeosciences, Multidisciplinary-
dc.relation.journalWebOfScienceCategoryRemote Sensing-
dc.relation.journalWebOfScienceCategoryImaging Science & Photographic Technology-
dc.subject.keywordPlusPROPELLER-
dc.subject.keywordAuthorlarge cavitation tunnel-
dc.subject.keywordAuthormodel test-
dc.subject.keywordAuthornoise localization-
dc.subject.keywordAuthorhydrophone array-
Files in This Item
There are no files associated with this item.
Appears in
Collections
선박연구본부 > Naval Ship Engineering Research Center > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Park, Young ha photo

Park, Young ha
지능형선박연구본부 (함정공학연구센터)
Read more

Altmetrics

Total Views & Downloads

BROWSE