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Modeling analysis and tuning of shunt piezoelectric damping controller for structural vibration

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Abstract

When the passive control technology is used to control the bending vibration of flexible structures, the shunt piezoelectric damping technology is commonly regarded as a straightforward and efficient approach. However, its performance is sensitive to the changes of the components' parameter values on the piezoelectric transducer, and usually requires more accurate tuning. This study introduces a novel optimization algorithm and criteria to optimize the parameters of the components in the shunt piezoelectric damping circuit. Specifically, the evaluation criteria for suppressing bending vibration are formulated using the frequency response and kinetic energy power spectrum. The improved Sine Cosine Algorithm (SCA) is then employed to optimize the parameters of the frequently used parallel, series, and negative capacitance impedance circuits. The accuracy of the model is verified by comparing the derived dynamic model and transfer function model with the results obtained from finite element software Workbench. Subsequently, the system's response is analyzed under different parameter values, damping conditions, and excitations. The convergence and feasibility of the improved SCA algorithm are demonstrated through an example that involves suppressing the bending vibration of a rectangular plate. Furthermore, the optimization calculation of component parameter values in the example circuit is conducted, and the results are compared with those obtained through previous methods, thereby affirming the effectiveness and advantages of the proposed algorithm for optimizing component parameter values in shunt piezoelectric damping circuits.

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Acknowledgements

This work was supported by the National Key R&D Program of China (No. 2019YFE0116200).

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Correspondence to Tao Wu.

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Wu, T., Chen, T., Yan, H. et al. Modeling analysis and tuning of shunt piezoelectric damping controller for structural vibration. Acta Mech 234, 4407–4426 (2023). https://doi.org/10.1007/s00707-023-03619-x

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  • DOI: https://doi.org/10.1007/s00707-023-03619-x

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