Experimental identification of NES parameters through Acceleration Surface Method
Résumé
Nonlinear Energy Sink (NES) have proven their efficiency to perform passive control of vibration, either in resonant or unstable dynamic situations [1]. Nevertheless, they require specific analytical computation to design proper parameters such as nonlinear stiffness and damping. If not well designed, they may create undesired responses, such as detached resonances. The realization of such purely nonlinear stiffness is challenging and the damping mechanism of such mechanical system is not mastered. Therefore, in industrial perspectives, after manufacturing, they would need a fast and easy wye to be identified. This paper proposes an experimental protocol to characterize and identify NES parameters. The characterization and identification of the non-linearities, stiffness and damping are essential for the NES. For this purpose, Acceleration Surface Method (ASM) is used [2,4]. This method links the acceleration of the NES with the relative displacement and velocity provided from measurements with accelerometers and laser vibrometer respectively. The advantage of this method is the use of the time history response of the mechanical system from a sine sweep run. Due to the zero linear stiffness and no natural frequency of the NES, the classical ASM has been adapted. The results allow identifying the stiffness and damping parameters of the NES, which validate the procedure proposed to treat each produced NES. References: [1] E. Gourc, G. Michon, S. Seguy, and A. Berlioz. Experimental Investigation and Design Optimization of Targeted Energy Transfer Under Periodic Forcing. Journal of Vibration and Acoustics, 136(2):021021, Apr. 2014. [2] Q. Liu, Z. Hou, Y. Zhang, X. Jing, G. Kerschen, and J. Cao. Nonlinear Restoring Force Identification of Strongly Nonlinear Structures by Displacement Measurement. Journal of Vibration and Acoustics, 144(3), Sept. 2021. [4] J. Noël and G. Kerschen. Nonlinear system identification in structural dynamics: 10 more years of progress. Mechanical Systems and Signal Processing, 83:2–35, Jan. 2017.