Model updating of damped structures using FRF data

Lin, Rong; Zhu, Jiaxin

doi:10.1016/j.ymssp.2006.05.008

Cited by 114 publications

(66 citation statements)

References 22 publications

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“…Differently, the FRF-based model updating methods make use of the measured FRFs directly which circumvent the need to identify the modal parameters from the experiments [12][13][14][15][16][17]. These methods are able to produce highly accurate updated system matrices through iteration.…”

Section: Introductionmentioning

confidence: 99%

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Model Updating of Spindle Systems Based on the Identification of Joint Dynamics

Cao

Cheng

2015

Shock and Vibration

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In order to simulate the cutting performance of a spindle mounted in the machine tool, the finite element (FE) model of spindles is required to be coupled with machine tool. However, the unknown joint dynamics (e.g., bolts) between the spindle and machine tool column limit the accuracy of the model. In this paper, an FE model updating method is proposed based on the identification of joint dynamics in both translational and rotational degrees-of-freedom (DOF). The receptance coupling (RC) technique is enhanced to estimate frequency response functions (FRFs) corresponding to rotational DOFs. The joint stiffness is identified through the iteration process by minimizing the difference between the simulated FRF and the measured FRF of the assembly. The proposed method is verified with a machine-tool spindle system. The good agreement between simulation and experiment shows the effectiveness of the method.

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Section: Introductionmentioning

confidence: 99%

“…In the second step, damping ratios were updated. Lin and Zhu [23] extended the response function method which is based on FRF data to update damping coefficients in addition to mass and stiffness matrices. Arora et al [24] proposed a damped model updating method using complex updating parameters.…”

Section: Introductionmentioning

confidence: 99%

Model Updating of Spindle Systems Based on the Identification of Joint Dynamics

Cao

Cheng

2015

Shock and Vibration

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“…The structural parameters are usually optimized using natural frequency and mode shape [4], flexibility matrix [5], responses in time-domain or frequencydomain [6], and so forth. Among the dynamic information, natural frequency reflects the most basic dynamic performance of the structure, and it can be identified easily, accurately, robustly, and reliably.…”

Section: Introductionmentioning

confidence: 99%

Structural Health Monitoring Based on Combined Structural Global and Local Frequencies

Hou

Jankowski

2014

Mathematical Problems in Engineering

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This paper presents a parameter estimation method for Structural Health Monitoring based on the combined measured structural global frequencies and structural local frequencies. First, the global test is experimented to obtain the low order modes which can reflect the global information of the structure. Secondly, the mass is added on the member of structure to increase the local dynamic characteristic and to make the member have local primary frequency, which belongs to structural local frequency and is sensitive to local parameters. Then the parameters of the structure can be optimized accurately using the combined structural global frequencies and structural local frequencies. The effectiveness and accuracy of the proposed method are verified by the experiment of a space truss.

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“…Moreover, correlations of analytical and experimental modes are commonly needed for mode shapes pairing. Compared with updating methods using modal parameters as input, methods using FRFs as input present several advantages (Esfandiari et al, 2009;Lin & Zhu, 2006), since several frequency data are available to set an over-determined system of equations, and no correlation analysis for mode pairing is necessary in general. Nevertheless there are some issues concerning the use of FRF residues, such as the number of measurement degrees of freedom (dofs), the selection of frequency data and the ill-conditioning of the resulting system of equations.…”

Section: Introductionmentioning

confidence: 99%