Estimates of Source Spectra of Ships from Long Term Recordings in the Baltic Sea
Estimates of the noise source spectra of ships based on long term measurements in the Baltic sea are presented. The measurement data were obtained by a hydrophone deployed near a major shipping lane south of the island Öland. Data from over 2,000 close-by passages were recorded during a 3 month peri...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2017-06-01
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| Series: | Frontiers in Marine Science |
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| Online Access: | http://journal.frontiersin.org/article/10.3389/fmars.2017.00164/full |
| _version_ | 1811284085734113280 |
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| author | Ilkka Karasalo Martin Östberg Peter Sigray Jukka-Pekka Jalkanen Lasse Johansson Mattias Liefvendahl Mattias Liefvendahl Rickard Bensow |
| author_facet | Ilkka Karasalo Martin Östberg Peter Sigray Jukka-Pekka Jalkanen Lasse Johansson Mattias Liefvendahl Mattias Liefvendahl Rickard Bensow |
| author_sort | Ilkka Karasalo |
| collection | DOAJ |
| description | Estimates of the noise source spectra of ships based on long term measurements in the Baltic sea are presented. The measurement data were obtained by a hydrophone deployed near a major shipping lane south of the island Öland. Data from over 2,000 close-by passages were recorded during a 3 month period from October to December 2014. For each passage, ship-to-hydrophone transmission loss (TL) spectra were computed by sound propagation modeling using
bathymetry data from the Baltic Sea Bathymetry Database (BSBD),sound speed profiles from the HIROMB oceanographic model,seabed parameters obtained by acoustic inversion of data from a calibrated source, andAIS data providing information on each ship's position.These TL spectra were then subtracted from the received noise spectra to estimate the free field source level (SL) spectra for each passage. The SL were compared to predictions by some existing models of noise emission from ships. Input parameters to the models, including e.g., ship length, width, speed, displacement, and engine mass, were obtained from AIS (Automatic Identification System) data and the STEAM database of the Finnish Metereological Institute (FMI). |
| first_indexed | 2024-04-13T02:23:19Z |
| format | Article |
| id | doaj.art-bf6b9d905f974b3ab18cee698384e22d |
| institution | Directory Open Access Journal |
| issn | 2296-7745 |
| language | English |
| last_indexed | 2024-04-13T02:23:19Z |
| publishDate | 2017-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Marine Science |
| spelling | doaj.art-bf6b9d905f974b3ab18cee698384e22d2022-12-22T03:06:53ZengFrontiers Media S.A.Frontiers in Marine Science2296-77452017-06-01410.3389/fmars.2017.00164252142Estimates of Source Spectra of Ships from Long Term Recordings in the Baltic SeaIlkka Karasalo0Martin Östberg1Peter Sigray2Jukka-Pekka Jalkanen3Lasse Johansson4Mattias Liefvendahl5Mattias Liefvendahl6Rickard Bensow7Underwater Technology, Defence and Security, Systems and Technology, Swedish Defense Research AgencyStockholm, SwedenUnderwater Technology, Defence and Security, Systems and Technology, Swedish Defense Research AgencyStockholm, SwedenUnderwater Technology, Defence and Security, Systems and Technology, Swedish Defense Research AgencyStockholm, SwedenDepartment of Atmospheric Composition Research, Finnish Meteorological InstituteHelsinki, FinlandDepartment of Atmospheric Composition Research, Finnish Meteorological InstituteHelsinki, FinlandUnderwater Technology, Defence and Security, Systems and Technology, Swedish Defense Research AgencyStockholm, SwedenDepartment of Mechanics and Maritime Sciences, Chalmers University of TechnologyGothenburg, SwedenDepartment of Mechanics and Maritime Sciences, Chalmers University of TechnologyGothenburg, SwedenEstimates of the noise source spectra of ships based on long term measurements in the Baltic sea are presented. The measurement data were obtained by a hydrophone deployed near a major shipping lane south of the island Öland. Data from over 2,000 close-by passages were recorded during a 3 month period from October to December 2014. For each passage, ship-to-hydrophone transmission loss (TL) spectra were computed by sound propagation modeling using bathymetry data from the Baltic Sea Bathymetry Database (BSBD),sound speed profiles from the HIROMB oceanographic model,seabed parameters obtained by acoustic inversion of data from a calibrated source, andAIS data providing information on each ship's position.These TL spectra were then subtracted from the received noise spectra to estimate the free field source level (SL) spectra for each passage. The SL were compared to predictions by some existing models of noise emission from ships. Input parameters to the models, including e.g., ship length, width, speed, displacement, and engine mass, were obtained from AIS (Automatic Identification System) data and the STEAM database of the Finnish Metereological Institute (FMI).http://journal.frontiersin.org/article/10.3389/fmars.2017.00164/fullship noiseunderwater radiated noiseURNAutomatic Identification SystemAISpropagation modeling |
| spellingShingle | Ilkka Karasalo Martin Östberg Peter Sigray Jukka-Pekka Jalkanen Lasse Johansson Mattias Liefvendahl Mattias Liefvendahl Rickard Bensow Estimates of Source Spectra of Ships from Long Term Recordings in the Baltic Sea Frontiers in Marine Science ship noise underwater radiated noise URN Automatic Identification System AIS propagation modeling |
| title | Estimates of Source Spectra of Ships from Long Term Recordings in the Baltic Sea |
| title_full | Estimates of Source Spectra of Ships from Long Term Recordings in the Baltic Sea |
| title_fullStr | Estimates of Source Spectra of Ships from Long Term Recordings in the Baltic Sea |
| title_full_unstemmed | Estimates of Source Spectra of Ships from Long Term Recordings in the Baltic Sea |
| title_short | Estimates of Source Spectra of Ships from Long Term Recordings in the Baltic Sea |
| title_sort | estimates of source spectra of ships from long term recordings in the baltic sea |
| topic | ship noise underwater radiated noise URN Automatic Identification System AIS propagation modeling |
| url | http://journal.frontiersin.org/article/10.3389/fmars.2017.00164/full |
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