UNDERWATERNOISEMAPPINGMETHODOLOGIESFORSHALLOWWATERS

Author:DavidSantos-Domínguez|Thesisadvisor:SoledadTorres-Guijarro|AffiliaIon:Sonitum(TSC,UniversidaddeVigo)

1.MoIvaIonoftheworko  MethodsforevaluaIonandquanIficaIonofunderwaternoise

needed.o  EuropeanNormaIve(2008/56/EC)asksforspecificsoluIonsbut

there’s no standard answer. EvaluaIon of the goodenvironmentalstatusoftheEuropeanwatersisneeded.

o  ECODRAGA experience calculaIng source level of a dredger.Environmental impact studies such as punta LangosteirablasIngsorVigoharborpilotdriving.

o  Shallow water propagaIon is complex and less invesIgated,goodexamples inourarea/locaIon:mulIpath,depthvariablespeedofsound,influenceofthebathymetryandseabed,etc.

2.ObjecIvesO1StudyandevaluaIonoftheunderwaternoisemeasurementmethodologies.

O2StudyandevaluaIonofPropagaIonLossescalculaIonO3StudyandcalibraIonofunderwaternoisepredicIonsocware.O4CharacterizaIonandclassificaIonofthedifferentnoisesourcesavailableinRíadeVigo.O5DevelopmentofnoisemapconstrucIonmethodologies.

O6ConstrucIonofanunderwaternoisemapofRíadeVigo.

3.Researchplan

1 Study about the state ofart of underwater noisem e a s u r e m e n tme thodo log i e s . U s i ngdatabases as sciencedirect,scopus,WOK,etc.

[Oct.2015-Feb.2016]

Figure1:UnderwaternoisemaprecreaIon

2 EvaluaIon of underwatern o i s e m e a s u r e m e n tm e t h o d o l o g i e s [ 1 ] [ 2 ] .Experimental measurements inshallow water. Development ofspecificmeasurementprotocols.

[Mar.2016-Jun.2016]

3Developmentofmethodsandp ro toco l s f o r c a l cu l aIngpropagaIon losses based onexperimental measurements.F ie ld measurements w i thcalibratedsource.

[Jul.2016-Oct.2016]

4 Underwater noise sourcesrecording. Measurement ofvarious sources of underwaternoiseinRíadeVigo.

[Jul.2016-Ago.2016]

6StudyofsocwarepropagaIonmodels.Comparison of experimental ands o c w a r e p r o p a g a I o n l o s s e smethodologies. CalibraIon of socwaremodels according to experimentalmeasurements.

[May.2017-Jun.2017]

7Studyofunderwaternoisemappingmethodologiesdevelopment. EvaluaIon of the usefulness of themodels obtained in the previous tasks for thedevelopment of underwater noisemaps, study of theuncertainty of the noise map data according to theuncertaintyoftheinputdatatothemodel.

Focusingon2soluAons

8DevelopmentofunderwaternoisemapoftheVigoestuary.ValidaIoncampaignsmeasurements:-2campaigns:summerandwinter-3to5daysofsampledmeasurements-3 different and simultaneous locaIonsawayfrommaintransit

[Sep.2017-Feb.2018]

4.ResultsanddiscussionTask3datahavebeenobtainedduringAdricristuydredgermeasurementssession[3]inMoañaharbour,Pontevedra:•  A methodology to calculate PropagaIon Losses, based on experimental measurements of the

measuredsourceandacalibratedsourceemikngtonesin1/3octavebands,wasestablished.•  A measurement set up and data processing were designed and successfully employed to provide

receivedlevelsatdifferentdepthsanddistancesfromthemeasuredandcalibratedsource.Task6wascompletedinconjuncIonwithtask3usingdifferentmodelsofprivatesocwaredBSea[4]:•  AmethodologytocalculatePropagaIonLosseswithdBSea,basedoncalibratedsourcelocaIonsand

fieldmeasurementdata,wasestablished.•  3 different solver algorithms were tested and a best fikng model, as a funcIon of distance and

frequency,wasobtained.Task 3 and 6 results have been presented atUACE 2015 [3]. Themost important research results aresyntheIzedinfigure2:ü  SLfikngbetweenboth experimental and socwaremethods is good from160-1000Hz, above1kHz

getsworsebutsIllacceptable.ü  In view of the results, the use of this socware to compute propagaIon losses is reasonable under

condiIons of reliable informaIon about bathymetry, sound speed profile and water and seafloorproperIes.

ü  FurtherworkisrequiredinordertogetaquanIficaIonofthevalidityoftheresultsdependingonthequanItyandqualityofdBSeaconfiguraIonparameters.

Figure2:ExperimentalvssocwareSLcalculaIon

Figure3:ShipsEaronlinesnapshot

5.References[1] ANSI/ASA S12.64-2009/Part 1, “Quantities and Procedures for Description and Measurement of Underwater Sound from Ships - Part 1: General Requirements”, American National Standards Institute, New York, (2009). [2] S P Robinson, P D Theobald, G Hayman, L S Wang, P A Lepper, V Humphrey, S Mumford, "Measurement of noise arising from marine aggregate dredging operations, Final Report. MALSF (MEPF Ref no. 09/P108)", Published by the MALSF, ISBN 978 0907545 57 6 (2011). [3] David Santos-Domínguez, Soledad Torres-Guijarro, Antonio Pena-Gimenez, “Analysis of dredger noise based on experimental and simulated source level calculations”, UACE2015 3rd Underwater Acoustics Conference and Exhibition 21st to 26th June 2015 Platanias, Crete, Greece. [4] “dBSea”, underwater acoustics prediction software, www.dbsea.co.uk/ [5] David Santos-Domínguez, Soledad Torres-Guijarro, Antonio Cardenal-López, Antonio Pena-Gimenez “ShipsEar: An underwater vessel noise database”, Applied Acoustics Volume 113, 1 December 2016, Pages 64–69.

Task4hasbeencompletedwithseveralmeasurementsessionsinRíadeVigoasexplainedin[5]:•  More than 100 recordings of 12 different type of vessels were obtained and accompanied by

descripIve details such as type of vessel, locaIonof the recording equipment,weather condiIons,etc.AnspecificmethodologyforthisrecordingcreaIonwasalsoestablished.

•  The sounds were recorded in real condiIons, so contain both natural and anthropogenicenvironmentalnoise.Theaimwastoprovideadatabaseofrealsoundsthatresearcherscoulduse,forexample,totrainvesseldetectorsandclassifiers.

Task5hasbeencompletedusingallthedataobtainedintask4:•  A selecIon of 90 recording was used to develop an online database with sound recordings

accompaniedbyfullydescripIvedetailsascanbeseeninfigure3.

Nextyearplanning…(7to8)FocusingonpossibiliIesofdBSeaandBellhop3DassocwaresoluIonsfornoisemapmodeling.CreaIonofRíadeVigounderwaternoisemapandvalidaIon troughmeasurementscampaigns.

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SL measured

SL_dBSea

•  Todemonstratetheusefulnessofthedatabase,avesselclassifierwasdeveloped,basedoncepstralcoefficientsandGMMs.

Mainresultsoftasks4and5havebeenpublishedinAppliedAcousIcs[5]:ü  ShipsEar,adatabaseofunderwatersoundsproducedbyvessels,withsoundrecordingsaccompanied

bydescripIvedetails suchas typeofvessel, locaIonof the recording,weathercondiIons,etc.Thisdatabasecanbeconsultedathnp://atlankc.uvigo.es/underwaternoise/.

ü  The 12 original vessel classes were merged into 4 classes and, using this distribuIon, the systemobtaineda75.4%classificaIonratewith100%accuracy indetecIngbackgroundnoiseand80%and76.5%classificaIonratesforthebestclasses.

ü  Further work: test more sophisIcated state-of-the-art algorithm for the classifier (SVMs or neuralnetworks);monitorvesselsposiIonsandimprovehydrophoneresponseatlowfrequencies.

5 ClassificaIon of the recordedsources. CreaIon of a detaileddatabase in web format using datafrom sources measurements task.Study and evaluaIon of automaIcclassifiers. Development of anautomaIc classifier tesIng theusefulnessofthedatabaseproposal.

[Nov.2016-Feb.2017]

dBSea-ConInuous/staIcsources,predictabletraffic.-3differentsolvers

Bellhop3D-RealIme/dynamicsources,unpredictabletraffic-Raytracingsolver

[Jul.2017-Agos.2017]