A robust-based configuration design method of piezoelectric materials for mechanical load identification considering structural vibration suppression

Liu, Yaru and Wang, Lei 2023. A robust-based configuration design method of piezoelectric materials for mechanical load identification considering structural vibration suppression. Computer Methods in Applied Mechanics and Engineering 410 , 115998. 10.1016/j.cma.2023.115998

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Abstract

Piezoelectric materials have received considerable attention to structural vibration suppression and health monitoring by virtue of their transform ability between electric energy and mechanical energy. This study investigates a novel robust-based configuration design method for piezoelectric materials under the assumption of identical configurations for actuator and sensor layers. Firstly, underlying the inverse piezoelectric effects, a load-independent layout design framework of piezoelectric actuators is developed in the context of topology optimization, in which the desired structural vibration suppression can be achieved and the robustness of system performance index representing actuating energies may be guaranteed once uncertainties are involved. Then, based on the direct piezoelectric effects, some piezoelectric sensors are effectively selected from the optimized distributed piezoelectric elements for mechanical load identification considering inevitable signal noises and material dispersion To improve the accuracy of identified results, an adaptive load identification method and an independence-driven sensor selection strategy are conducted. To strengthen the robustness of identified results, an uncertain-oriented load identification method and variance-driven sensor selection strategy are completed. Moreover, interval quantification and propagation methods are adopted to deal with multi-source uncertainties. Eventually, two numerical examples are discussed to demonstrate the validity and feasibility of the developed approach.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Engineering
Additional Information:	License information from Publisher: LICENSE 1: URL: http://creativecommons.org/licenses/by-nc-nd/4.0/, Start Date: 2025-03-26
Publisher:	Elsevier
ISSN:	0045-7825
Date of Acceptance:	9 March 2023
Last Modified:	29 Mar 2023 09:30
URI:	https://orca.cardiff.ac.uk/id/eprint/158158

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