Research Papers

Elimination of Bias Errors Due to Suspension Effects in FRF-Based Rigid Body Property Identification

[+] Author and Article Information
Robert Kloepper1

Department of Mechanical and Aerospace Engineering, Tokyo Institute of Technology, 2-12-1-I3-15 Ookayama, Meguro-ku, Tokyo 152-8552, Japankloepper.r.aa@m.titech.ac.jp

Masaaki Okuma

Department of Mechanical and Aerospace Engineering, Tokyo Institute of Technology, 2-12-1-I3-15 Ookayama, Meguro-ku, Tokyo 152-8552, Japan

It is noted in Ref. 11 that the suspension model did not describe the actual suspension behavior and that accurate results were obtained in a frequency range where the suspension effect was minimal. As possible explanations for the suspension model’s ineffectiveness, the authors offer that (a) the rotational stiffness of the spring elements had been neglected and that (b) the experimental conditions may have been different from the test conditions of the spring elements. It seems likely to us that preload effects contributed to (b). In Ref. 10, only results of simulations are presented that did not include gravity effects.

Lau and Deblauwe referred to the elastic assumption as the “corrected FRF” method (16). In the context of this paper, this expression would be confusing because not only the correction of elastic mode effects is considered but also the correction of suspension effects.

It would have been difficult to determine the 0 Hz value and the almost coinciding resonances frequencies at 0.37 Hz and 0.38 Hz experimentally. The five resonance frequencies are not required by the identification algorithm and are mentioned only with the purpose of specifying the suspension properties.


Corresponding author.

J. Dyn. Sys., Meas., Control 131(4), 041005 (Apr 29, 2009) (10 pages) doi:10.1115/1.3089564 History: Received February 24, 2008; Revised December 21, 2008; Published April 29, 2009

The prediction of a mechanical structure’s rigid dynamic behavior requires knowledge of ten inertia parameters. In cases where no accurate models of the structure’s geometry and mass distribution are available, the ten inertia parameters must be determined experimentally. Experimental methods based on measurements of frequency response functions (FRFs) are subject to bias errors due to suspension effects. This paper proposes a method for eliminating these errors by using a single-wire suspension condition and modeling the suspension’s effect on the FRFs. The suspension model depends only on the unknown rigid body properties and on three easy-to-measure parameters. The rigid body properties are determined by fitting FRFs derived from the suspension model and from the rigid body mass matrix directly to the experimental FRF data. Eliminating the suspension bias makes it possible to use low-frequency FRF data, which in turn justifies the assumption of rigid behavior. In this way, bias-free rigid body property identification can be achieved without modal curve fitting. Simulation and experimental results are presented showing the effectiveness of the approach.

Copyright © 2009 by American Society of Mechanical Engineers
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Figure 1

Example for the FRF of a softly suspended structure

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Figure 5

FE model of the shell structure used as test Case 3

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Figure 6

Simulation results for the aluminum beam structure (test Case 1)

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Figure 7

Simulation results for the weakened beam structure (test Case 2)

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Figure 8

Simulation results for the shell structure (test Case 3)

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Figure 9

Experimental setup (a) and sensor attachment for the measurement of ωV (b)

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Figure 10

Experimental results for the aluminum beam structure

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Figure 11

Excitation and response DOFs used in evaluating errors in the predicted rigid body accelerance

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Figure 4

FRFs and modal curve fitting results for the different test cases

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Figure 3

FE model of the beam structure used in the test Cases 1 and 2

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Figure 2

Geometric relationships of the single-wire suspension condition



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