Numerical calculation for determining sonar self noise sources due to structural vibration

Musha, Takaaki; Kikuchi, Tatsuo

doi:10.1016/s0003-682x(98)00073-5

Cited by 7 publications

(4 citation statements)

References 4 publications

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“…where, let k e [3,5 ] , A N e L4, I0_',, and let k and AN get a large number if there is a large sample and many variables will be used to train network. In this network, the number of hidden layer nodes N = 55.…”

Section: Decision Of Network Structurementioning

confidence: 99%

Underwater vehicle sonar self-noise prediction based on genetic algorithms and neural network

Zhong-kun

2006

J Mar. Sc. Appl.

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Section: Decision Of Network Structurementioning

confidence: 99%

Underwater vehicle sonar self-noise prediction based on genetic algorithms and neural network

Zhong-kun

2006

J Mar. Sc. Appl.

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“…The sources of mechanical selfnoise might be multiple such as vibrating machines on the ship which diffuse vibration energy or second excitation of structure-borne sound. However, it is essential to comprehend the characteristics of interaction between the enclosed water sound field and its elastic boundary structures for the purpose of prediction, evaluation, and control of interior hydroacoustic noise [3].…”

Section: Introductionmentioning

confidence: 99%

Research on Power Flow Transmission through Elastic Structure into a Fluid-Filled Enclosure

Rui

Jing

et al. 2018

Advances in Acoustics and Vibration

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The work of this paper is backgrounded by prediction or evaluation and control of mechanical self-noise in sonar array cavity. The vibratory power flow transmission analysis is applied to reveal the overall vibration level of the fluid-structural coupled system. Through modal coupling analysis on the fluid-structural vibration of the fluid-filled enclosure with elastic boundaries, an efficient computational method is deduced to determine the vibratory power flow generated by exterior excitations on the outside surface of the elastic structure, including the total power flow entering into the fluid-structural coupled system and the net power flow transmitted into the hydroacoustic field. Characteristics of the coupled natural frequencies and modals are investigated by a numerical example of a rectangular water-filled cavity with five acoustic rigid walls and one elastic panel. Influential factors of power flow transmission characteristics are further discussed with the purpose of overall evaluation and reduction of the cavity water sound energy.

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“…At present, many the self-noise in sonar problem discussions are in the majority with hydrodynamic noise, however, the mechanical noise problem also can't be ignored and particularly important for the low-speed submarine underwater navigation.Musha et al Literature [1] proposed a method to determine the self-noise of sonar caused by turbulence by using a simplified acoustic vibration transfer function. Literature [2,3,4]based on the rectangular cavity model used the statistical energy method and the modal method to calculate and analyze the hydrodynamic component of sonar self-noise; In the literature [5], the low frequency (10Hz~500Hz) self-noise of the platform area is predicted by using the finite element modeling of sonar platform area structure and empirical radiation coefficient.…”

Section: Introductionmentioning

confidence: 99%

Hydroacoustic field in sonar cavity under mechanical excitations

Wang¹,

Rui²,

Wang³

2016

Proceedings of the 2016 6th International Conference on Advanced Design and Manufacturing Engineering (ICADME 2016)

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Abstract. In view of the destructive influence of mechanical self-noise on sonar's detection capability at lower frequencies, a parametric model composed of panels and a water filled rectangular cavity is established for investigation of characteristics of hydroacoustic field caused by mechanical excitation loaded on sonar platform area. The analytical derivation and numerical simulation analysis of differential vibration equations provide theoretical reference for prediction and control of mechanical self-noise.

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Numerical calculation for determining sonar self noise sources due to structural vibration

Cited by 7 publications

References 4 publications

Underwater vehicle sonar self-noise prediction based on genetic algorithms and neural network

Underwater vehicle sonar self-noise prediction based on genetic algorithms and neural network

Research on Power Flow Transmission through Elastic Structure into a Fluid-Filled Enclosure

Hydroacoustic field in sonar cavity under mechanical excitations

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