Analysis of underwater acoustic and electric noise in the port of Gothenburg

Petrovic, S.; Dalberg, E.; Lennartsson, R.K.; Persson, Leif

doi:10.1109/oceans.2008.5151929

Cited by 6 publications

(3 citation statements)

References 8 publications

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“…The feasibility of passive acoustic detection in a cluttered harbor and a coastal environment remains an outstanding question, a limited number of previous studies and projects [10], [11], have addressed these questions. For the overview of background and previous work, Chapter 2 will detail the development process.…”

Section: Scope Of Researchmentioning

confidence: 99%

“…Stolkin R. et al [10], measured soniferous fishes and a diver's breathing sound, discriminate threat presence by the threshold value. Morrissey R et al [34], used spectrogram analysis, matched filters and neural networks methods to accomplish realtime detection and localization of vocalizing marine animals.…”

Section: Divers and Underwater Animals Passive Detectionmentioning

confidence: 99%

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Passive acoustic detection of a small remotely operated vehicle

Cai

Bingham

2011

OCEANS 2011 IEEE - Spain

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This project quantifies the feasibility of passive acoustic detection of a small commercial off-the-shelf (COTS) remotely operated vehicle (ROV) by experimentally characterizing the acoustic signature and hydrodynamic flow associated with the motion of ROV.Three experiments are conducted as parts of this characterization in this project.These trials are conducted in a small laboratory test tank, a larger outdoor test tank and a shallow-water coastal ocean environment. The laboratory tank test consists of a stationary hydrophone to detect the acoustic emissions, while simultaneously measuring the flow field using particle image velocimetry (PIV) system. Based on a variety of maneuvers in the test tank, the experiments are quantified by the acoustic signatures of the ROV. Also, we predict the capabilities of acoustically detecting an ROV in typical ocean environments such as shallow-water, ports and harbors, and deep-ocean environment. In addition, this thesis reports the results of a series of underwater detection trials in the field to verify the laboratory demonstration and analytical moderns. The intention is to experimentally measure the signal-to-noise ratio (SNR) of the ROV acoustic signature, as a function of distance between the ROV and acoustic receivers in the shallow-water ocean environment.On the basis of experimental analysis, we present that the most significant contribution for ROV acoustic detection is from electric motors with signal frequency range of around 400-500 Hz. The detectable distance range with ambient noise at 116 dB re 1 uPa is between 15 m and 22 m away in a noisy littoral environment. Combined with the experimental analysis, we state the comparison between the acoustic predicted levels of the ROV with the measured results.Finally, this project demonstrates the feasibilities of acoustical detection of a small ROV in the port environment. As a result, we conclude the experimental studies with later highlights and future research.iii DEDICATION To my dearest dad, mom and the whole familyWho love me and support me unconditionally iv ACKNOWLEDGMENTS

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Section: Scope Of Researchmentioning

confidence: 99%

Section: Divers and Underwater Animals Passive Detectionmentioning

confidence: 99%

Passive acoustic detection of a small remotely operated vehicle

Cai

Bingham

2011

OCEANS 2011 IEEE - Spain

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“…The passive detection of vessels and marine wildlife has been the subject of much research, but diver detection has received little attention. Diver signals have very different characteristics and they typically have low signal levels [7].…”

Section: Introductionmentioning

confidence: 99%

Passive energy based acoustic signal analysis for diver detection

Lohrasbipeydeh

Dakin

Gulliver

et al. 2014

2014 Oceans - St. John's

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A passive energy based analysis of the acoustic signal from a diver is presented. The frequency components of the signal during inhaling and exhaling are investigated, as well as the periodicity of the signal features. The effect of different regulators on the power spectral density of the signals is evaluated. The energy based detection problem is formulated using the timefrequency Teager Energy Operator (TEO) as it can be used to develop an adaptive detector. To evaluate the proposed approach, experimental data is employed which was recorded in the open ocean at different ranges and depths. This data was obtained using accurate hydrophones provided by Ocean Network Canada (ONC).Index Terms-Diver acoustic signals, Inhaling and exhaling signals, Energy based detection, Bubble oscillation.978-1-4799-4918-2/14/$31.00 ©2014 IEEE

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