A General Data-Based Approach for Developing Reduced-Order Models of Nonlinear MDOF Systems
- 174 Downloads
A general procedure is presented for analyzing dynamic response measurements from complex multi-degree-of-freedom nonlinear systems incorporating arbitrary types of nonlinear elements. The analysis procedure develops a reduced-order, nonlinear model whose format is convenient for numerical simulation studies. No information about the system’s mass properties is needed, and only the applied excitations and corresponding response are needed to develop the model whose dimension is compatible with the number of available sensors. The utility of the approach is demonstrated by means of a three-degree-of-freedom system incorporating polynomial-type nonlinear features with hardening as well as softening characteristics.
Key wordsidentification modeling nonlinear systems simulation validation
Unable to display preview. Download preview PDF.
- 2.Housner, G. W., Bergman, L. A., Caughey, T. K., Chassiakos, A. G., Claus, R. O., Masri, S. F., Skelton, R. E., Soong, T. T., Spencer, B. F., and Yao, J. T. P., ‘Structural control: Past, present and future’, ASCE Journal of Engineering Mechanics (Special Issue) 123(9), 1997, 897–971.CrossRefGoogle Scholar
- 4.Worden, K. and Tomlinson, G. R., Nonlinearity in Structural Dynamics: Detection, Identification and Modelling, Institute of Physics, London, 2001.Google Scholar
- 6.Masri, S. F., Miller, R. K., Saud, A. F., and Caughey, T. K., ‘Identification of nonlinear vibrating structures; Part I: Formulation’, ASME Journal of Applied Mechanics 109, December 1987, 918–922; “Part II: Applications”, 923–929.Google Scholar
- 8.Smyth, A. W. and Pei, J.-S., ‘Integration of measured response signals for nonlinear structural health monitoring’, in Proceedings of the 3rd US-Japan Workshop on Nonlinear System Identification and Health Monitoring, Los Angeles, California, October 20–21, 2000.Google Scholar