Detecting Inception of Hydrodynamic Cavitation Noise of Ships using Quadratic Phase Coupling Index as an Indicator

Sandhya, M. K.; Rajarajeswari, K.; Seetaramaiah, P.

doi:10.14429/dsj.65.7885

Cited by 8 publications

(4 citation statements)

References 8 publications

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“…The main sources of ship radiated sound are: (1) machinery noise generated by propulsion and auxiliary machinery such as engines, main motors and gears; (2) propeller noise generated by cavitation at or near the propeller and propeller-induced resonant hull excitation; (3) hydrodynamic noise from radiated flow noise, resonant excitation of cavities, plates, and appendages; and (4) cavitation at struts and appendages. The passive acoustic spectra of ship-radiated sound is extremely dynamic, containing both broadband signals and narrowband tonals at discrete frequencies [23,41] with source levels that can vary depending on ship conditions [42,47] such as ship speed [48][49][50], orientation [39] and maneuvers [51]. Ship noise has been previously found to be dominated by propeller cavitation, propeller singing due to physical excitation at the trailing edges of the blades, and propulsion or other reciprocating machinery [2,8,18,28,45,46].…”

Section: Introductionmentioning

confidence: 99%

Continental Shelf-Scale Passive Acoustic Detection and Characterization of Diesel-Electric Ships Using a Coherent Hydrophone Array

et al. 2017

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The passive ocean acoustic waveguide remote sensing (POAWRS) technique is employed to detect and characterize the underwater sound radiated from three scientific research and fishing vessels received at long ranges on a large-aperture densely-sampled horizontal coherent hydrophone array. The sounds radiated from the research vessel (RV) Delaware II in the Gulf of Maine, and the RV Johan Hjort and the fishing vessel (FV) Artus in the Norwegian Sea are found to be dominated by distinct narrowband tonals and cyclostationary signals in the 150 Hz to 2000 Hz frequency range. The source levels of these signals are estimated by correcting the received pressure levels for transmission losses modeled using a calibrated parabolic equation-based acoustic propagation model for random range-dependent ocean waveguides. The probability of the detection region for the most prominent signal radiated by each ship is estimated and shown to extend over areas spanning roughly 200 km in diameter when employing a coherent hydrophone array. The current standard procedure for quantifying ship-radiated sound source levels via one-third octave bandwidth intensity averaging smoothes over the prominent tonals radiated by a ship that can stand 10 to 30 dB above the local broadband level, which may lead to inaccurate or incorrect assessments of the impact of ship-radiated sound.

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Section: Introductionmentioning

confidence: 99%

Continental Shelf-Scale Passive Acoustic Detection and Characterization of Diesel-Electric Ships Using a Coherent Hydrophone Array

et al. 2017

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“…e results showed acceptable accuracy in the predictions of the pump's remaining useful life. Sandhya et al [26] introduced and used a phase coupling index through bispectrum to detect the onset of cavitation of a ship propeller. ey experimentally measured the noise data from a ship propeller and showed the effectiveness of their proposed method.…”

Section: Introductionmentioning

confidence: 99%

Cavitation Analysis in Centrifugal Pumps Based on Vibration Bispectrum and Transfer Learning

Hajnayeb

2021

Shock and Vibration

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Detection of cavitation in centrifugal pumps is critical in their condition monitoring. In order to detect cavitation more accurately and confidently, more advanced signal processing techniques are needed. For the classification of a pump conditions based on the outputs of these techniques, advanced machine learning techniques are needed. In this research, an automatic system for cavitation detection is proposed based on machine learning. Bispectral analysis is used for analyzing the vibration signals. The resulting bispectrum images are given to convolutional neural networks (CNNs) as inputs. The CNNs are a pretrained AlexNet and a pretrained GoogleNet, which are used in this application through transfer learning. On the contrary, a laboratory test setup is used for generating controlled cavitation in a centrifugal pump. The suggested algorithm is implemented on the vibration dataset acquired from the laboratory pump test setup. The results show that the cavitation state of the pump can be detected accurately using this system without any need to image processing or feature extraction.

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“…The types of cavitation that can occur on the wing vary, including tip vortex cavitation, sheet cavitation, cloud cavitation, hub cavitation, etc. Tip vortex cavitation is known to be the first to occur among these various types, so the tip vortex cavitation can be considered as the most important factor to predict and determine the Cavitation Inception Speed (CIS), and various studies have been conducted to detect 1,2 it and delay 3,4 it.…”

Section: Introductionmentioning

confidence: 99%

Establishment of cavitation inception speed judgment criteria by cavitation noise analysis for underwater vehicles

Jeong

Hong

Song

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part M:

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Cavitation occurs on objects that move underwater at high speeds, and it is accompanied by an increase in hull vibrations, a reduction in propulsion performance, and an increase in noise that is important for warships and submarines. Of the various types of cavitations, tip vortex cavitations (TVC) are the earliest occurring and are considered the most important in terms of cavitation inception speed (CIS). This study predicts the cavitation inception speed by conducting cavitation noise analyses. The trend of the noise according to the cavitation numbers before and after CIS was analysed, and the quantitative criteria to determine the CIS were presented through established procedures. The CIS value obtained through the analysis was verified by comparing it against the value obtained experimentally. The methods used to analyse the cavitation inception speed are developed using bubble dynamics for cavitation noises. First, flow-field information was obtained downstream of the wing to estimate the external force acting on the bubbles, and this was used to calculate the behaviour of the cavitation bubbles. The bubble dynamics analyses were performed for each cavitation nuclei by Lagrange approach to calculate the behaviour of the bubbles. The number of cavitation nuclei was calculated based on the density function with random placement upstream of the wing. The cavitation noise was analysed for various cavitation numbers, and the tendency of the noise generated for each case was investigated. The noise analysis results and the CIS predictions were compared and verified with the measured values in the Large Cavitation Tunnel (LCT) of the Korea Research Institute of Ship & Ocean Engineering (KRISO). Using these results, the effect of the tip vortex cavitation on the total flow noise was analysed, and CIS determination criteria using noise values was validated and established.

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Detecting Inception of Hydrodynamic Cavitation Noise of Ships using Quadratic Phase Coupling Index as an Indicator

Cited by 8 publications

References 8 publications

Continental Shelf-Scale Passive Acoustic Detection and Characterization of Diesel-Electric Ships Using a Coherent Hydrophone Array

Continental Shelf-Scale Passive Acoustic Detection and Characterization of Diesel-Electric Ships Using a Coherent Hydrophone Array

Cavitation Analysis in Centrifugal Pumps Based on Vibration Bispectrum and Transfer Learning

Establishment of cavitation inception speed judgment criteria by cavitation noise analysis for underwater vehicles

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