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Model and Parameters Identification of Non-Linear Joint by Force-State Mapping in Frequency Domain

Published online by Cambridge University Press:  05 May 2011

J.-H. Wang  and
H.-Y. Huang
J.-H. Wang*
Affiliation:
Sound and Vibration Labarotories, Department of Power Mechanical Engineering, National Tsing Hua University, Hsinchu, Taiwan 30013, R.O.C.
H.-Y. Huang*
Affiliation:
Sound and Vibration Labarotories, Department of Power Mechanical Engineering, National Tsing Hua University, Hsinchu, Taiwan 30013, R.O.C.
*
* Professor
** Graduate student
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Abstract

Generally, the Force-State Mapping (FSM) is an effective method to identify the parameters of nonlinear joints provided that the joint model is exactly known in advance. However, the variation of the non-linear joints is so large that the mathematical models of non-linear joints generally are not known in advance. Therefore, the model and the parameters of a non-linear joint should be identified simultaneously in practice. In this work, a new identification procedure which was based on the FSM method in frequency domain was proposed to identify the mathematical model and parameters of a non-linear joint simultaneously. Generally, there are many feasible combinations of models and parameters which can satisfy the measurement data within an allowable range of error. In this work, an iteration procedure was used to update the feasible models to result in an optimal model with its parameters. The simulation results show that a proper mathematical model and accurate parameters can be identified simultaneously by the new procedure even that the measurement data are contaminated by noise.

Keywords

Non-linear jointModel identificationParameter identification
Type
Articles
Information
Journal of Mechanics , Volume 23 , Issue 4 , December 2007 , pp. 367 - 380
Copyright
Copyright © The Society of Theoretical and Applied Mechanics, R.O.C. 2007

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References

1.Yuan, J. X. and Wu, X. M., “Identification of the Joint Structural Parameters of Machine Tool by DDS and FEM,” ASME, J. of Engineering for Industries, 107, pp. 64–69 (1985).CrossRefGoogle Scholar
2.Ren, R., and Beards, C. F., “Identification of Effective Linear Joints Using Coupling and Joint Identification Techniques, ASME, J. of Vibration and Acoustics, 121, pp. 331–338 (1998).CrossRefGoogle Scholar
3.Ratcliffe, M. J. and Lieven, N. A. J., “A Generic Element-Based Method for Joint Identification,” Mechanical System and Signal Processing, 14, pp. 3–28 (2000).CrossRefGoogle Scholar
4.Wang, J. H. and Liou, C. M., “Identification of Parameters of Structural Joints by Use of Noise-Contaminated FRFs,” J. of Sound and Vibration, 142, pp. 261–277(1990).Google Scholar
5.Wang, J. H. and Chuang, S. C., “Reducing Errors in the Identification of Structural Joint Parameters Using Error Functions,” J. of Sound and Vibration, 273, pp. 295–316(2004).CrossRefGoogle Scholar
6.Masri, S. F. and Caughey, T. K., “A Nonparametric Identification Technique for Nonlinear Dynamic Problem,” ASME, J. of Applied Mechanics, 46, pp. 433–447 (1979).CrossRefGoogle Scholar
7.Ren, Y., Lim, T. M. and Lim, M. K., “Identification of Properties of Nonlinear Joints Using Dynamic Test Data,” ASME, J. of Vibration and Acoustics, 120, pp. 324–330 (1998).CrossRefGoogle Scholar
8.Crawley, E. F. and Aubert, A. C., “Identification of Non-Linear Structural Element by Force-State Mapping,” AIAA Journal, 24, pp. 155–162 (1986).Google Scholar
9.Crawley, E. F. and O'Donnell, K. J., “Force-State Mapping Identification of Nonlinear Joints,” AIAA Journal, 25, pp. 1003–1010 (1987).CrossRefGoogle Scholar
10.Al-Hadid, M. A. and Wright, J. R., “Application of the Force-State Mapping Approach to the Identification of Non-linear Systems,” Mechanical Systems and Signal Processing, 4, pp. 463–482 (1990).Google Scholar
11.Al-Hadid, M. A. and Wright, J. R., “Estimation of Mass and Modal Mass in the Identification of Nonlinear Single and Multi Degree of Freedom Systems Using the Force-State Mapping Approach,” Mechanical Systems and Signal Processing, 6, pp. 383–401 (1992).CrossRefGoogle Scholar
12.Kim, W. J. and Park, Y. S., “Non-linear Joint Parameters Identification by Applying the Force-State Mapping Technique in the Frequency Domain,” Mechanical System and Signal Processing, 8, pp. 519–529 (1994).CrossRefGoogle Scholar
13.Hansen, P. C. and O'Leary, , “The Use of L-Curve in the Regularization of Discrete Ill-Posed Problems,” SIAM Journal of Scientific Computing, 14, pp. 1487–1503 (1993).CrossRefGoogle Scholar
14.Hansen, P. C.Regularization tools: A Matlab package for analysis and solution of discrete ill-posed problem, Numerical Algorithms, 6, pp. 1–35 (1994).CrossRefGoogle Scholar
15.Berger, E. J., “Friction Modeling for Dynamic System Simulation,” Applied Mechanics Reviews, 55, pp. 535–577 (2002).Google Scholar
16. Matlab: User's Manual of Math Works Inc.Google Scholar