Structural model updating using frequency response function and quasi-linear sensitivity equation

Esfandiari, Akbar; Bakhtiari-Nejad, Firooz; Rahai, Alireza; Sanayei, Masoud

doi:10.1016/j.jsv.2009.07.001

Cited by 122 publications

(70 citation statements)

References 34 publications

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“…Even though this technique requires the knowledge of the excitation forces (and thus require forced excitations), FRFs are sometimes preferred over modal data as additional errors due to the modal analysis procedure are avoided [33]. The use of FRFs in the modal updating process requires, in addition, an estimation of the modal damping ratios, as these can in general not be very accurately predicted.…”

Section: Vibration-based Fe Model Updating 221 Experimental Datamentioning

confidence: 99%

Dealing with uncertainty in model updating for damage assessment: A review

Simoen

Roeck

Lombaert

2015

Mechanical Systems and Signal Processing

397

217

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In structural engineering, model updating is often used for non-destructive damage assessment: by calibrating stiffness parameters of finite element models based on experimentally obtained (modal) data, structural damage can be identified, quantified and located. However, the model updating problem is an inverse problem prone to ill-posedness and ill-conditioning. This means the problem is extremely sensitive to small errors, which may potentially detract from the method's robustness and reliability. As many errors or uncertainties are present in model updating, both regarding the measurements as well as the employed numerical model, it is important to take these uncertainties suitably into account. This paper aims to provide an overview of the available approaches to this end, where two methods are treated in detail: a non-probabilistic fuzzy approach and a probabilistic Bayesian approach. These methods are both elaborated for the specific case of vibration-based finite element model updating for damage assessment purposes.

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Section: Vibration-based Fe Model Updating 221 Experimental Datamentioning

confidence: 99%

Dealing with uncertainty in model updating for damage assessment: A review

Simoen

Roeck

Lombaert

2015

Mechanical Systems and Signal Processing

397

217

View full text Add to dashboard Cite

show abstract

“…Other methods use FRF measurements directly, as opposed to the modal data extracted from the FRF measurements. 22,23 The authors argued that the FRF data can provide much more information on damage in a desired frequency range compared to modal data that is extracted with errors from a very limited range around resonance.…”

Section: Introductionmentioning

confidence: 99%

Application of Improved Accelerated Random Search Algorithm for Structural Damage Detection

Boubakir¹,

Touat²,

Kharoubi³

et al. 2017

IJAV

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Finite element (FE) model updating technique belongs to the class of inverse problems in classical mechanics. According to the continuum damage mechanics, damage is represented by a reduction factor of the element stiffness and mass. The objective of the optimization problem is to minimize the difference between measured and numerical FE vibration data. In this study a new method is presented for structural damage detection called Improved Modified Accelerated Random Search algorithm (IMARS). The algorithm uses model updating procedure to detect damages in a decoupled fashion. First, detecting the location and the number of damaged elements is evaluated by multi-run process. Knowing damage number, the quantification step is then applied using simple computing procedure. The effectiveness of the algorithm is first tested on mathematical benchmark functions. The algorithm is then applied in damage detection of 2D beam structure and 2D truss structure. These two cases have different boundary conditions and different damage scenarios. The simulated experimental modal data have been taken as reference values. A real cantilever beam with experimental modal parameters is used to validate the proposed method for real single and double damages. Results show that the proposed method is accurate and robust in structural damage identification.

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“…It should be noticed that structure parameters and damping parameters are separated into different network levels, which reduced the numerical affection of parameters on each other. Esfandiari [13] used error residuals of transfer function too, but separated the sensitivity matrix by stiffness and mass, which provides more parameters to be updated. Later in [14], measured strain data were used to get the transfer function needed by the updating, but the transformation process was too complicated for complex actual structures.…”

Section: Introductionmentioning

confidence: 99%

Finite element model updating of damped structures using vibration test data under base excitation

Yuan

2015

Journal of Sound and Vibration

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Structural model updating using frequency response function and quasi-linear sensitivity equation

Cited by 122 publications

References 34 publications

Dealing with uncertainty in model updating for damage assessment: A review

Dealing with uncertainty in model updating for damage assessment: A review

Application of Improved Accelerated Random Search Algorithm for Structural Damage Detection

Finite element model updating of damped structures using vibration test data under base excitation

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