In this paper, the continuous wavelet transform based on the Mor let-wavelet function is used to identify the modal damping ratios of multi-degree-offreedom vibration systems. A new wavelet-based method for the damping identification from measured free responses is presented. The proposed method was also tested by experiments on a steel beam. | Vietnam Journal of Mechanics, VAST, Vol. 27, No. 1 (2005), pp. 41 - 50 DAMPING IDENTIFICATION IN MULTI-DEGREE-OF-FREEDOM SYSTEMS USING THE CONTINUOUS WAVELET TRANSFORM NGUYEN PHONG DIEN Hanoi University of Technology A bstract . The identification of damping in multi-degree-of-freedom vibration systems is a well-known problem and appears to be of crucial interest. Compared to an estimation of the stiffness and mass, the damping coefficient or, alternatively, damping ratio is the most difficult quantity to determine. In this paper, the continuous wavelet transform based on the Mor let-wavelet function is used to identify the modal damping ratios of multi-degree-offreedom vibration systems. A new wavelet-based method for the damping identification from measured free responses is presented. The proposed method was also tested by experiments on a steel beam. 1. INT RODUCTION The identification of damping in multi-degree-of-freedom vibration systems is a wellknown problem and appears to be of crucial interest . Compared to an estimation of the stiffness and mass, the damping coefficient or, alternatively, damping ratio is the most difficult quantity to determine. While both mass and stiffness can be determined by static tests, damping requires a dynamic test to measure. The majority of damping measurements performed today are based on experimental modal analysis or modal testing [8] . However, this approach requires a specific measurement hardware and a complex software for determining the frequency response function of the system and extracting t he modal data. Furthermore, the frequency response functions will often give significant errors resulting from the influence of the noise and the spectrum overlap . Over t he past 10 years, wavelet theory has become one of the emerging and fastevolving mathematical and signal processing tool for its many distinct merits . General overview of application of the wavelet transform may be found in [2, 6, 7]. The .
