scholarly journals Estimation of beam material random field properties via sensitivity-based model updating using experimental frequency response functions

2018 ◽  
Vol 102 ◽  
pp. 180-197 ◽  
Author(s):  
M.R. Machado ◽  
S. Adhikari ◽  
J.M.C. Dos Santos ◽  
J.R.F. Arruda
2018 ◽  
Vol 22 (4) ◽  
pp. 935-947 ◽  
Author(s):  
Qianhui Pu ◽  
Yu Hong ◽  
Liangjun Chen ◽  
Shili Yang ◽  
Xikun Xu

This article evaluates the use of experimental frequency response functions for damage detection and quantification of a concrete beam with the help of model updating theory. The approach is formulated as an optimization problem that intends to adjust the analytical frequency response functions from a benchmark finite element model to match with the experimental frequency response functions from the damaged structure. Neither model expansion nor reduction is needed because the individual analytical frequency response function formulation is derived. Unlike the commonly used approaches that assume zero damping or viscous damping for simplicity, a more realistic hysteretic damping model is considered in the analytical frequency response function formulation. The accuracy and anti-noise ability of the proposed approach are first verified by the numerical simulations. Next, a laboratory reinforced concrete beam with different levels of damage is utilized to investigate the applicability in an actual test. The results show successful damage quantification and damping updating of the beam by matching the analytical frequency response functions with the experimental frequency response functions in each damage scenario.


2018 ◽  
Vol 211 ◽  
pp. 06005
Author(s):  
Tiago Silva ◽  
João Pereira

In the field of structural dynamics is common to predict the behaviour of a structure regarding structural modifications. In this context, the frequency based substructuring method is well-known to perform structural modifications based on the coupling of structures. This process gives the possibility to perform the study of a structure at the level of its components and then assess the response of the coupled system. In practice, it is impossible to attain an experimental complete response model, although one can simulate all the responses of a structure using numerical models. Hence, the substructuring process can be enhanced by the combined use of experimental and numerical responses, as it was demonstrated using numerically obtained frequency response functions. This work presents the enhancement of the frequency based substructuring method using a method to expand experimental frequency response functions over the entire set of degrees of freedom in a finite element model. This expansion process, known as modified Kidder’s method, considers that if one can only measure translations due to exciting force, it is possible to obtain the complete response model, including the rotational frequency response functions due to exciting moments. The combined use of the frequency based substructuring and the modified Kidder’s methods has several advantages, as it avoids modal identification or residual compensation. To evaluate the performance of the proposed procedure a numerical example of a beam structure is presented, and its results are discussed.


2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Hong Yin ◽  
Zenghui Wang ◽  
Mingming Cao ◽  
Zhenrui Peng ◽  
Kangli Dong

Aiming at the problems that Markov chain Monte Carlo algorithm is not easy to converge, has high rejection rate, and is easy to be disturbed by the noise when the parameter dimension is high, an improved model updating method combining the singular values of frequency response functions and the beetle antennae search algorithm is proposed. Firstly, the Latin hypercube sampling is used to extract the training samples. The Hankel matrix is reconstructed using the calculated frequency response functions and is decomposed by singular value decomposition. The effective singular values are retained to represent the frequency response functions. Secondly, according to the training samples and the corresponding singular values, the support vector machine surrogate model is fitted and its accuracy is tested. Then, the posterior probability distribution of parameters is estimated by introducing the beetle antennae search algorithm on the basis of standard Metropolis–Hastings algorithm to improve the performance of Markov chains and the ergodicity of samples. The results of examples show that the Markov chains have better overall performance and the acceptance rate of candidate samples is increased after updating. Even if the Gaussian white noise is introduced into the test frequency response functions under the single and multiple working damage conditions, satisfactory updating results can also be obtained.


Author(s):  
T P Waters ◽  
N A J Lieven

Measured frequency response functions (FRFs) are becoming more widely used to correlate finite element (FE) models with test structures. However, most model updating techniques require measured data at every degree of freedom (DOF) in the FE model, a necessity that is rarely met by experiment. Furthermore, the sensitivity of updating techniques to noise measurement demands experimental data of the highest attainable quality, and often beyond. A modified surface spline is presented which can expand measured FRFs to unmeasured DOFs and also apply smoothing to reduce noise contamination.


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