HOMOTOPY CONTINUATION ALGORITHM FOR STRUCTURAL DAMAGE IDENTIFICATION

I. INTRODUCTIONStructural damages due to the loss of sti?ness such as crack, localization bulking have remarkablein?uences on the physical properties of structure such as deformation, stress, frequency and modelshape. So the change of these properties can be used to identify the damage location and degree ofstructures. The damage identification techniques based on these properties’ changes have attractedmuch attention in recent years, and many approaches have been developed[1??5].Nowaday…     

Parametric identification of nonlinear systems using multiple trials

It is observed that the harmonic balance (HB) method of parametric identification of nonlinear system may not give right identification results for a single test data. A multiple-trial HB scheme is suggested to obtain improved results in the identification, compared with a single sample test. Several independent tests are conducted by subjecting the system to a range of harmonic excitations. The individual data sets are combined to obtain the matrix for inversion. This leads to the mean square error minimization of the entire set of periodic orbits. It is shown that the combination of independent test data gives correct results even in the case where the individual data sets give wrong results.     

Partial Uniqueness and Obstruction to Uniqueness in Inverse Problems for Anisotropic Elastic Media

We consider the inverse problem of identifying the density and elastic moduli for three-dimensional anisotropic elastic bodies, given displacement and traction measurements made at their surface. These surface measurements are modelled by the dynamic Dirichlet-to-Neumann map on a finite time interval. For linear or nonlinear anisotropic hyperelastic bodies we show that the displacement-to-traction surface measurements do not change when the density and elasticity tensor in the interior are transformed tensorially by a change of coordinates fixing the surface of the body to first order. Our main tool, a new approach in inverse problems for elastic media, is the representation of the equations of motion in a covariant form (following Marsden and Hughes, 1983) that preserves the underlying physics.In the case of classical linear elastodynamics we then investigate how the type of anisotropy changes under coordinate transformations. That is, we analyze the orbits of general linear, anisotropic elasticity tensors under the action by pull-back of diffeomorphisms that fix the surface of the elastic body to first order, and derive a pointwise characterization of parts of the orbits under this action. For example, we show that the orbit of isotropic elastic media, at any point in the body, consists of some transversely isotropic and some orthotropic elastic media. We then derive the first uniqueness result in the inverse problem for anisotropic media using surface displacement-traction data: uniqueness of three elastic moduli for tensors in the orbit of isotropic elasticity tensors. ^†Partially supported by an MSRI Postdoctoral Fellowship. Research at MSRI is supported in part by NSF grant DMS-9850361. This work was conducted while the first author was a Gibbs Instructor at Yale University. ^‡Partially supported by an MSRI Postdoctoral Fellowship, and by NSF grant DMS-9801664 (9996350).     

一种不受相位噪声影响的模态参数识别法

本文提出了一种根据幅值频响数据来识别模态参数的频域识别法.该方法首先通过识别幅值频响函数模型来得到传递函数的零点和极点.鉴于不同结构系统可以有完全相同的幅值频响函数,文中提出了由相位频响数据来判定传递函数零点的号性,以唯一确定传递函数,从而消除了相位噪声对模态参数识别结果的影响.作为例子,文中给出了计算机模拟实验例子和滚动轴承支承动态参数识别的应用实例.     

Research on the algorithm of binary image cross-correlation for unsteady flow field measurement

In the present paper, the algorithm of Binary Image Cross-Correlation (BICC) was developed to measure the unsteady flow field. A vortex flow field was used to test the algorithm by numerical simulation. The results show that BICC is an effective algorithm for particle identification from consecutive images, the accurate velocity vector field can be obtained. The real velocity field in a valve chamber was measured by BICC in this study. From the full-field velocity information, the pressure and vorticity fields were also extracted by post-processing. The project supported by the National Natural Science Foundation of China     

Identification of Cavities Inside Two-Dimensional Heterogeneous Isotropic Elastic Bodies

In this paper, we discuss the uniqueness in determining cavities (i.e., nonrectilinear cracks) in a heterogeneous isotropic elastic medium in two dimensions. Our main result asserts that there is at most one cavity in the elastic medium which yields the same surface displacements and stresses on an arbitarily small portion of the boundary. The boundaries of cavities are assumed to be piecewise smooth and admit edges where no net force is exerted. The key of the proof is the unique continuation for the isotropic Lamé system and geometric considerations. This revised version was published online in August 2006 with corrections to the Cover Date.     

Minimal dynamic characterization of tree-like multibody systems

The dynamic model of tree-like multibody systems is linear with respect to the parameters of mass distribution for instance when barycentric parameters are used. Thus, assuming that the parameters related to the kinematics are perfectly known, these quantities can be estimated through linear regression techniques. The necessary data are obtained by measuring the joint forces and/or torques and the resulting motion given in terms of positions, velocities and accelerations. An alternative method uses measurements of the reaction forces and torques applied to the bedplate.The linearity of the dynamic and reaction models with respect to the barycentric quantities does not however imply that the latter constitute the minimum set of parameters characterizing the mass distribution of the system. In other words, some barycentric parameters may disappear from the models or may be redundant in the sense that they appear only via linear combinations. In the first case they are not identifiable, while in the second case the linear regression technique leads to estimated values which are correct for the combinations but can be erroneous for the individual parameters.The various options taken to derive the dynamic and reaction models by use of the ROBOTRAN programme are briefly reviewed. Then the rules leading to the minimal parametrization are presented and illustrated by means of a practical example related to a robot calibration problem.     

In-situ mechanical properties identification of 3D particulate composites using the Virtual Fields Method

This paper presents an identification procedure based on the Virtual Fields Method (VFM) for identifying in situ mechanical properties of composite materials constitutive phases from 3D full-field measurements. The new procedure, called the Regularized Virtual Fields Method (RVFM), improves the accuracy of the VFM thanks to the imposition of mechanical constraints derived from an appropriate homogenization model. The developed algorithms were validated through virtual experiments on particulate composites. The robustness of both the VFM and the RVFM was assessed in the presence of noisy strain data for various microstructures. A study was also carried out to investigate the influence of the size of region of interests on the reliability of the identified parameters. Accordingly, the optimum size of region of interest was determined based on full-field measurement requirements and accuracy of the identified parameters. This study enables determining, a priori, the required magnification level of 3D images for composites of any mechanical and morphological characteristics.     

Optimal Conditional Estimation: Average Case Setting

We consider an estimation problem which appears in the identification of systems by means of restricted complexity models: find the optimal approximation to an element of a linear normed space (a system) based on noisy information, subject to the restriction that approximations (models) can be selected from a prescribed subspace M of the problem element space. In contrast to the worst-case optimization criterion, which may be pessimistic, in this paper the quality of an identification algorithm is measured by its local average performance. Two types of local average errors are considered: for a given information (measurement) y and for a given unknown element x, the latter in two versions. For a wide spectrum of norms in the measurement space, we define an optimal algorithm and give expressions for its average errors which show the dependence on information, information errors, unmodelled dynamics, and norm in the measurement space.     

Direct and Inverse Problems for a Phase-Field Model with Memory

We consider a semilinear integrodifferential system in non-normal form. Such a system is a generalization of the one that arises in the phase-field theory with memory. We prove an abstract existence and uniqueness theorem and a continuous dependence result for the direct problem. Reformulating the direct problem in a suitable way we prove that the identification problem admits a unique solution.