STRUCTURE-BORNE SOUND SOURCE MODEL AS A PRE-PROCESSOR FOR STATISTICAL ENERGY ANALYSIS: SuBSS-SEA Pre-processor

结构声源模型作为统计能量分析的预处理器:SubBSS-SEA 预处理器

基本信息

  • 批准号:
    EP/D00215X/1
  • 负责人:
  • 金额:
    $ 11.57万
  • 依托单位:
  • 依托单位国家:
    英国
  • 项目类别:
    Research Grant
  • 财政年份:
    2006
  • 资助国家:
    英国
  • 起止时间:
    2006 至 无数据
  • 项目状态:
    已结题

项目摘要

Statistical Energy Analysis (SEA) was introduced in the 1960s to predict if rocket payloads (satelites, delicate instruments) would be damaged by the vibration of the rocket during flight. Since then, SEA has been used to predict the vibration and noise created by structures when in operation, such as automobiles, aircraft, trains, ships, buildings, offshore structures and domestic appliances. It remains the only widely used calculation method for high frequencies and complicated structures. It is particularly useful in predicting how vibrations and sound travel through the structure.It works well if the cause of the vibration is airborne e.g. loudspeakers, fans, air flow noise, but less well for vibrating machines directly connected to the structure, e.g. motors, pumps, compressors; these are known as structure-borne sources. This is because the machine's vibrations transmit to the supporting/surrounding structure in a complicated combination of motions. Also, thin lightweight structures will vibrate more than heavy structures when connected to the same vibrating machines, so we need to know as much about the structure (the receiver) as about the machine (the source). As a result, there is not at present a practical method of estimating the strength of a machine's vibration such that the noise and vibration which it causes when it is installed can be predicted.This application seeks to bring together three centres of expertise to work on this problem; the Dynamics Group of the Institute of Sound and Vibration Research of Southampton University; the Acoustics Research Centre of Salford University; the Acoustics Research Unit of the University of Liverpool.The aim of the project is to develop a way of obtaining data on the strength of structure-borne sources, which can be used as input to SEA models of vehicles, buildings, appliances, etc., to predict the vibration and noise when the source is installed. The research will answer the following three questions:What do manufacturers of machines and machine components need to measure in order to obtain the strength of these structure-borne sound sources? How can this source data be organised and simplified in order to be understandable by engineers using SEA computer programs?How much information, on those parts of the vehicle, building, etc., which are connected to the vibrating machine, do we require to predict the vibration energy being transmitted?
统计能量分析(SEA)是在20世纪60年代引入的,用于预测火箭有效载荷(卫星,精密仪器)是否会在飞行期间被火箭的振动损坏。从那时起,SEA已被用于预测结构在运行时产生的振动和噪声,如汽车,飞机,火车,船舶,建筑物,海上结构和家用电器。它仍然是高频和复杂结构唯一广泛使用的计算方法。它在预测振动和声音如何在结构中传播时特别有用。如果振动的原因是空气传播的,例如扬声器,风扇,气流噪声,它工作得很好,但对于直接连接到结构的振动机器,例如电机,泵,压缩机,则不太好;这些被称为结构传播源。这是因为机器的振动以复杂的运动组合传递到支撑/周围结构。此外,当连接到相同的振动机器时,薄的轻质结构将比重型结构振动更多,因此我们需要了解结构(接收器)以及机器(源)。因此,目前还没有一种实用的方法来估计机器的振动强度,以便可以预测机器安装时引起的噪声和振动。利物浦大学声学研究单位。该项目的目的是开发一种获取结构源强度数据的方法,这些数据可用作车辆、建筑物、电器等的SEA模型的输入,预测安装时的振动和噪声。该研究将回答以下三个问题:机器和机器部件制造商需要测量什么才能获得这些结构声源的强度?如何组织和简化这些源数据,以便使用SEA计算机程序的工程师能够理解?有多少关于车辆、建筑物等部件的信息,连接到振动机上,我们是否需要预测传递的振动能量?

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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Brian Mace其他文献

Vibration suppression performance of parallel magnetic nonlinear energy sinks under impulse excitations
  • DOI:
    10.1016/j.ymssp.2024.111810
  • 发表时间:
    2025-01-01
  • 期刊:
  • 影响因子:
  • 作者:
    Muxuan Guo;Lihua Tang;Brian Mace;Daniel J. Inman
  • 通讯作者:
    Daniel J. Inman
Prediction of sound transmission through plates using spectral Gaussian basis functions and application to plates with periodic acoustic black holes
使用频谱高斯基函数预测板的声传播及其在具有周期性声学黑洞的板中的应用
  • DOI:
    10.1016/j.jsv.2025.118952
  • 发表时间:
    2025-06-09
  • 期刊:
  • 影响因子:
    4.900
  • 作者:
    Yi Yang;Michael Kingan;Brian Mace
  • 通讯作者:
    Brian Mace
Correction to: Dynamic analysis of the response of Duffing-type oscillators subject to interacting parametric and external excitations
  • DOI:
    10.1007/s11071-021-07047-1
  • 发表时间:
    2021-11-19
  • 期刊:
  • 影响因子:
    6.000
  • 作者:
    Mehrdad Aghamohammadi;Vladislav Sorokin;Brian Mace
  • 通讯作者:
    Brian Mace

Brian Mace的其他文献

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{{ truncateString('Brian Mace', 18)}}的其他基金

Estimation of structural dynamic parameters at higher frequencies using Bayesian methods
使用贝叶斯方法估计较高频率下的结构动态参数
  • 批准号:
    EP/G056765/1
  • 财政年份:
    2009
  • 资助金额:
    $ 11.57万
  • 项目类别:
    Research Grant

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