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

基本信息

批准号：
EP/G056765/1
负责人：
Brian Mace
金额：
$ 36.22万
依托单位：
University of Southampton
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2009
资助国家：
英国
起止时间：
2009 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FG056765%2F1
关键词：
Estimation structural dynamic parameters higher

项目摘要

This proposal concerns the vibrations of complex structures such as cars and aircraft at higher frequencies, typically in the audio-frequency range. The engineer must be able to design safe, reliable and efficient structures which have acceptable noise and vibration performance. There is an increasing reliance on computers to develop numerical models of the system. However, the numerical model must be validated by comparing its behaviour with that of the real structure, estimating the parameters of the model from the measurements, and updating the numerical model so that it gives accurate predictions in which the engineer has confidence.One aspect of this problem is central to the proposal: that where there is substantial uncertainty in the properties of one or more parts of the structure. This uncertainty arises from inevitable manufacturing variability. For example, when a product is made, it always differs from the engineer's idealisation. The effects of uncertainty grow as frequency increases so that, for the applications under consideration, it must be taken into account.This research concerns two main applications. Both involve estimating the parameters of a structure using Bayesian methods. These methods require prior knowledge of the distributions of the uncertainties, and there are a number of ways in which these prior distributions can be estimated: empirically, in terms of modes of vibration and from numerical (finite element) analysis, for example.The first main application concerns the mid-frequency range, where neither of the most common conventional methods of vibration analysis (finite element (FE) analysis and statistical energy analysis (SEA)) are, on their own, able to model the behaviour of the structure. It is only recently that hybrid methods have been developed which can model such situations. Typical applications are to structures where stiff, load-bearing components are connected to flexible panels: a car, which has both thin, flexible body panels and stiff frames; an aircraft, which comprises stiff frames and spars and a thin, flexible skin. The stiff component is sometimes referred to as the master substructure while the flexible parts form fuzzy substructures. The aim here is to estimate the properties of the master substructure from measurements taken of the whole structure, to allow detailed, FE numerical models of the master to be validated and parameters updated to yield a refined model.The second main application concerns the case where fuzzy substructures are coupled. This situation is suitable for SEA. The parameters which describe the interaction (so-called coupling loss factors or energy influence coefficients) are often found by numerical or physical experiment. It is proposed here that Bayesian methods will be developed to allow for accurate, robust estimation of these parameters.Some methods of damage detection attempt to infer its presence by monitoring changes in the vibrational behaviour of the structure. A third application concerns detection of possible damage in the master substructure of a fuzzy structure - a fatigue crack in a wing spar, for example. The presence of the fuzzy substructures clouds the vibration of the master. Using the methods developed in this project they can be removed and the vibrational behaviour of the master substructure alone recovered. This can perhaps then be used for damage detection.The methods will be validated and illustrated by numerical and physical experiments and by application to engineering structures.

该提案涉及复杂结构的振动，例如汽车和飞机，通常在音频频率范围内。工程师必须能够设计具有可接受的噪声和振动性能的安全，可靠和高效的结构。越来越多地依赖计算机来开发系统的数值模型。但是，必须通过将其行为与真实结构的行为进行比较，从测量结果估算模型的参数并更新数值模型来验证数值模型，以便对工程师具有信心的准确预测。该问题的一个方面是提案的至关重要的：在一个或更多部分或更多部分结构的属性中存在很大的不确定性。这种不确定性来自不可避免的制造可变性。例如，当制造产品时，它总是不同于工程师的理想化。随着频率的增加，不确定性的影响会增加，因此，对于所考虑的应用，必须考虑到它。这项研究涉及两个主要应用。两者都涉及使用贝叶斯方法估算结构的参数。这些方法需要先验了解不确定性的分布，并且可以通过多种方式可以估算这些先前的分布：从经验上讲，根据振动模式和数值（有限元）分析，例如，第一个主要应用程序，第一个主要应用程序。第一个主要应用都涉及中频率范围，而在最常见的传统元素（自身）分析（有限的）分析（FE）的情况下（FE）分析（FE）（FE）（FE）（fe）（FE）（FE）（FE）（FE）（FE）（FE）（FE）（FE）（FE）（FE）（FE）（FE）范围（FE）范围结构的行为。直到最近，已经开发了混合方法才能对这种情况进行建模。典型的应用是在结构上连接到柔性面板的结构：一辆既有薄，柔性的车身面板又有僵硬的框架的汽车；飞机包括僵硬的框架和翼梁以及薄而柔软的皮肤。刚性组件有时称为主结构，而灵活的零件形成模糊的子结构。这里的目的是从对整个结构的测量值中估算主子结构的属性，以允许对主的详细数值模型进行验证，并更新参数以产生精致的模型。第二个主要应用程序涉及模糊子结构的情况。这种情况适合海洋。描述相互作用（所谓的耦合损耗因子或能量影响系数）的参数通常是通过数值或物理实验找到的。这里建议将开发贝叶斯方法，以允许对这些参数进行准确，可靠的估计。一些损伤检测方法尝试通过监视结构的振动行为的变化来推断其存在。第三个应用程序涉及检测模糊结构的主结构中可能的损害 - 例如，机翼晶石中的疲劳裂纹。模糊子结构的存在使主的振动蒙上了阴影。使用该项目中开发的方法可以去除它们，并且单独恢复了主体结构的振动行为。也许可以将其用于损害检测。该方法将通过数值和物理实验以及对工程结构的应用来验证和说明。