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Parametric Analysis of Ship Noise Spectra.

Authors :
Traverso, Federico
Gaggero, Tomaso
Tani, Giorgio
Rizzuto, Enrico
Trucco, Andrea
Viviani, Michele
Source :
IEEE Journal of Oceanic Engineering; Apr2017, Vol. 42 Issue 2, p424-438, 15p
Publication Year :
2017

Abstract

A growing attention has been recently devoted to the impact of the underwater noise field generated by shipping activities on the marine fauna. A key aspect for the quantification of such impact is a proper model of the source levels radiated from the vessels. At a first level of approximation, simplified formulations based on a small number of macroparameters describing the ship characteristics are needed to quantify the emission and, accordingly, assess the noise impact and evaluate strategies for its control. In fact, a few models of this kind are available in the literature, mainly based on measurements and databases developed for military purposes. Most of these models have been tuned on old ships: this poses the question whether they are still applicable to modern commercial vessels. In this work, spectra of a series of measurements of underwater noise emitted by commercial vessels measured in the framework of two EU FP7 projects (SILENV: <uri>www.silenv.eu</uri> and AQUO: <uri>www.aquo.eu</uri>) are analyzed and compared with the results obtained applying the available literature models. The analysis is carried out for noise emitted both at design and off-design conditions. In such conditions, the models are also compared with a proposed spectral parametrization. Focusing on the off-design conditions, a detailed narrow band analysis of a complete set of noise spectra is presented for a ship equipped with a controllable pitch propeller (CPP). The spectral peculiarities of such a propulsion plant, when operated at constant revolutions per minute (RPM) are highlighted. Results of the suggested parametrization applied to the same ship are presented together with the data of other CPP ships and a critical analysis is carried out discussing the limits of the existing predictive models. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03649059
Volume :
42
Issue :
2
Database :
Complementary Index
Journal :
IEEE Journal of Oceanic Engineering
Publication Type :
Academic Journal
Accession number :
122577440
Full Text :
https://doi.org/10.1109/JOE.2016.2583798