A study on performance of distributed piezoelectric composite actuators using Galerkin method
Source abstract
Abstract
Abstract Piezoelectric ceramic actuators have been recognized as a valuable path to control the deformation and vibration of intelligent structures. However, the inherent brittle nature of piezoelectric ceramics limits the application of the piezoelectric ceramic actuators. In this paper, the novel distributed piezoelectric composite actuators (DPCA) made of the fiber reinforced piezoelectric composite (FRPC) are proposed to improve the mechanical properties and actuation performance of the piezoelectric actuators. A smart beam structure composed of a simply supported beam and the DPCA is utilized to research the actuation performance of the DPCA. The expression for the driving moment of the DPCA is obtained through electro-mechanical coupling theory. Based on Euler–Bernoulli beam theory, the differential governing equation of the smart beam is derived. The numerical solutions for the deflection of the smart beam are procured by the Galerkin method, and the current method is validated by comparison with the finite element simulation solutions. The actuation performance of the DPCA and its influencing factors are numerically analyzed through the proposed method. The numerical results show that the DPCA have good actuation performance and can realize the various deformations of the smart beam. The deflection of the smart beam can be increased obviously by choosing the reasonable electric field, fiber volume fraction, simply supported beam height, height and spacing of the piezoelectric actuators. Furthermore, the proposed theoretical method has the advantages of simplicity, practicability and flexibility, and has a certain guiding significance for the engineering application of the piezoelectric actuators.
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Research context
OpenAlex topics: Aeroelasticity and Vibration Control · Acoustic Wave Phenomena Research · Composite Structure Analysis and Optimization
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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