The effect of modulation of high frequency ship noise by propeller rotation frequencies is well known. This modulation is observed with the Detection of Envelope Modulation on Noise (DEMON) algorithm. Analysis of the DEMON spectrum allows the revolutions per minute and number of blades of the propeller to be determined. This work shows that the high frequency noise of a small boat can also be modulated by engine frequencies. Prior studies have not reported high frequency noise amplitude modulated at engine frequencies. This modulation is likely produced by bubbles from the engine exhaust system.
Marine vessel propellers produce noise by the formation and shedding of cavitation bubbles. This process creates both narrow-band tones and broad-band amplitude modulated noise. The Detection of Envelope Modulation on Noise (DEMON) is an algorithm to determine the frequencies that modulate this noise. Results of DEMON processing depend on the selection of a ship noise frequency band to analyze. It is well known that the best passband to use may vary dramatically between vessels. Despite this, there has been no systematic investigation how the DEMON spectra depend of the carrier noise frequencies, and the modulation indices of vessel noise have not been investigated. We use a modification of the Cyclic Modulation Spectrum (CMS) to determine the modulation index of cavitation noise across the entire spectrum of carrier frequencies. We investigated how speed and vessel size affect the modulation index and carrier frequency of vessel noise. Several phenomena in the distribution of modulation indices for large and small boats were observed. These can be used for vessel classification. For small boats, the DEMON spectra have a different set of frequency peaks at various carrier frequencies. This is explained by the engine exhaust which produces amplitude modulated noise much like a propeller.
The Detection of Envelope Modulation on Noise (DEMON) algorithm is a widely used tool in underwater passive acoustics for the detection and classification of vessel sound. The DEMON algorithm extracts the frequencies that modulate the high frequency cavitation noise created by a vessel’s propeller. We propose an extension of the DEMON method for time delay estimations of acoustic signals received by two or more hydrophones. This method, based on the phase difference between components in the two DEMON spectra received by different hydrophones, allows the extraction of the Time Difference Of Arrival (TDOA) and direction of arrival of the modulated signals. This method was applied to the acoustic signatures of six small boats collected by Stevens in a large glacial lake in NJ and showed agreement with the traditional cross-correlation method of TDOA estimation and boat GPS tracks. This method allows the separation of several boats TDOA. The DEMON algorithm also provides information of potential use for vessel classification. [This work was supported by DHS’s S&T Directorate.]
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