Estimation of Modal Parameters Confidence Intervals: A Simple Numerical Example

Detection of Concrete Spalling Using Changes in Modal Flexibility

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.163-167.2598 ◽

2010 ◽

Vol 163-167 ◽

pp. 2598-2602

Author(s):

Nadia Hajihasani ◽

Norhisham Bakhary

Keyword(s):

Natural Frequencies ◽

Mode Shapes ◽

Modal Parameters ◽

Dynamic Parameters ◽

Numerical Example ◽

Damage Location ◽

Modal Flexibility ◽

Vibration Parameters

This paper presents a study in the effect of spalling to dynamic parameters such as natural frequencies and mode shapes. Numerical example of a slab is used as an example in this study. The slab will be modelled using ANSYS 11.0 and various types of spalling are imposed. The changes of vibration parameters are monitored and compared. To compare the sensitivity of modal parameters to spalling is determined using the flexibility method. Based on the results it is found that by incorporating mode shapes using flexibility method, damage location and severity can be obtained.

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An Efficient Method for Compensating Truncated Higher Modes in Structural Dynamics Modification

Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science ◽

10.1243/pime_proc_1986_200_092_02 ◽

1986 ◽

Vol 200 (1) ◽

pp. 41-48 ◽

Cited By ~ 1

Author(s):

K R Chung ◽

C W Lee

Keyword(s):

Structural Dynamics ◽

Efficient Method ◽

Curve Fitting ◽

Modal Parameters ◽

Frequency Range ◽

Single Degree Of Freedom ◽

Higher Modes ◽

Numerical Example ◽

Single Degree ◽

Damped Systems

An efficient method for compensating the effects of the truncated higher modes in structural dynamics modification (SDM) is developed to predict the accurate modal parameters of locally modified structures. The effects of the truncated higher modes are represented by a fictitious, effective mode residing beyond the frequency range of interest. The modal parameters are then easily obtained by the iterative single degree-of-freedom curve-fitting technique developed for lightly damped systems. A numerical example demonstrates the effectiveness of the improved SDM technique.

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Confidence Intervals of Modal Parameters during Progressive Damage Test

Linking Models and Experiments, Volume 2 - Conference Proceedings of the Society for Experimental Mechanics Series ◽

10.1007/978-1-4419-9305-2_17 ◽

2011 ◽

pp. 237-250 ◽

Cited By ~ 2

Author(s):

Michael Döhler ◽

Falk Hille ◽

Xuan-Binh Lam ◽

Laurent Mevel ◽

Werner Rücker

Keyword(s):

Confidence Intervals ◽

Modal Parameters ◽

Progressive Damage

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A New Maximum Likelihood Estimator Formulated in Pole-Residue Modal Model

Applied Sciences ◽

10.3390/app9153120 ◽

2019 ◽

Vol 9 (15) ◽

pp. 3120

Author(s):

Sandro Amador ◽

Mahmoud El-Kafafy ◽

Álvaro Cunha ◽

Rune Brincker

Keyword(s):

Maximum Likelihood ◽

Least Squares ◽

Maximum Likelihood Estimator ◽

Confidence Intervals ◽

Modal Parameters ◽

Parameter Estimates ◽

Modal Parameter ◽

Likelihood Estimator ◽

Pole Residue ◽

Modal Model

Recently, a lot of efforts have been devoted to developing more precise Modal Parameter Estimation (MPE) techniques. This is explained by the necessity in civil, mechanical and aerospace engineering of obtaining accurate estimates for the modal parameters of the tested structures, as well as of determining reliable confidence intervals for these estimates. The Non-linear Least Squares (NLS) identification techniques based on Maximum Likelihood (ML) have been increasingly used in modal analysis to improve precision of estimates provided by the Least Squares (LS) based estimators when they are not accurate enough. Apart from providing more accurate estimates, the main advantage of the ML estimators, with regard to their LS counterparts, is that they allow for taking into account not only the measured Frequency Response Functions (FRFs) but also the noise information during the parametric identification process and, therefore, provide the modal parameters estimates together with their uncertainties bounds. In this paper, a new derivation of a Maximum Likelihood Estimator formulated in Pole-residue Modal Model (MLE-PMM) is presented. The proposed formulation is meant to be used in combination with the Least Squares Frequency Domain (LSCF) to improve the precision of the modal parameter estimates and compute their confidence intervals. Aiming at demonstrating the efficiency of the proposed approach, it is applied to two simulated examples in the final part of the paper.

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