Mechanical self-noise prediction of sonar parts based on equivalent excitation spectrum theory

Y. B. Sun; R. Huo

doi:10.1088/1757-899X/504/1/012056

Mechanical self-noise prediction of sonar parts based on equivalent excitation spectrum theory

Y. B. Sun
, R. Huo^*

^*Corresponding author for this work

Shandong University

Research output: Contribution to journal › Conference article › peer-review

1 Citation (Scopus)

Abstract

The mechanical self-noise of the sonar is one of the important factors affecting the performance of the sonar. Therefore, studying the prediction of the mechanical self-noise of the sonar is of far-reaching significance for the effective performance of sonar detection. In this paper, the theoretical modeling of the propagation channel is carried out, and the transfer characteristics of the excitation of the vibration source device into the sonar platform region are numerically simulated. A method for predicting the mechanical self-noise of the sonar part based on the equivalent excitation spectrum analysis is proposed.

Original language	English
Article number	012056
Journal	IOP Conference Series: Materials Science and Engineering
Volume	504
Issue number	1
DOIs	https://doi.org/10.1088/1757-899X/504/1/012056
Publication status	Published - 26 Apr 2019
Externally published	Yes
Event	2nd International Workshop on Materials Science and Mechanical Engineering, IWMSME 2018 - Qingdao, China Duration: 26 Oct 2018 → 28 Oct 2018

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10.1088/1757-899X/504/1/012056

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title = "Mechanical self-noise prediction of sonar parts based on equivalent excitation spectrum theory",

abstract = "The mechanical self-noise of the sonar is one of the important factors affecting the performance of the sonar. Therefore, studying the prediction of the mechanical self-noise of the sonar is of far-reaching significance for the effective performance of sonar detection. In this paper, the theoretical modeling of the propagation channel is carried out, and the transfer characteristics of the excitation of the vibration source device into the sonar platform region are numerically simulated. A method for predicting the mechanical self-noise of the sonar part based on the equivalent excitation spectrum analysis is proposed.",

author = "Sun, \{Y. B.\} and R. Huo",

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AU - Sun, Y. B.

AU - Huo, R.

N1 - Publisher Copyright: © Published under licence by IOP Publishing Ltd.

PY - 2019/4/26

Y1 - 2019/4/26

N2 - The mechanical self-noise of the sonar is one of the important factors affecting the performance of the sonar. Therefore, studying the prediction of the mechanical self-noise of the sonar is of far-reaching significance for the effective performance of sonar detection. In this paper, the theoretical modeling of the propagation channel is carried out, and the transfer characteristics of the excitation of the vibration source device into the sonar platform region are numerically simulated. A method for predicting the mechanical self-noise of the sonar part based on the equivalent excitation spectrum analysis is proposed.

AB - The mechanical self-noise of the sonar is one of the important factors affecting the performance of the sonar. Therefore, studying the prediction of the mechanical self-noise of the sonar is of far-reaching significance for the effective performance of sonar detection. In this paper, the theoretical modeling of the propagation channel is carried out, and the transfer characteristics of the excitation of the vibration source device into the sonar platform region are numerically simulated. A method for predicting the mechanical self-noise of the sonar part based on the equivalent excitation spectrum analysis is proposed.

UR - https://www.scopus.com/pages/publications/85065595215

U2 - 10.1088/1757-899X/504/1/012056

DO - 10.1088/1757-899X/504/1/012056

M3 - Conference article

AN - SCOPUS:85065595215

SN - 1757-8981

VL - 504

JO - IOP Conference Series: Materials Science and Engineering

JF - IOP Conference Series: Materials Science and Engineering

IS - 1

M1 - 012056

T2 - 2nd International Workshop on Materials Science and Mechanical Engineering, IWMSME 2018

Y2 - 26 October 2018 through 28 October 2018

ER -

Mechanical self-noise prediction of sonar parts based on equivalent excitation spectrum theory

Abstract

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