The optimal placement of piezoelectric actuator and sensor for active structural noise control of plates

Abstract The location optimization of actuators and sensors is a very important step when applying Active Structure Acoustic Control to practical engineering. A good actuator arrangement not only achieves a more effective control effect, but also reduces the required control energy, and a good senso...

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Bibliographic Details
Published inSmart materials and structures Vol. 31; no. 9; pp. 95028 - 95042
Main Authors Wu, Tao, Chen, Zhaobo, Qu, Jianjun, Yu, Dong
Format Journal Article
LanguageEnglish
Published IOP Publishing 01.09.2022
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Summary:Abstract The location optimization of actuators and sensors is a very important step when applying Active Structure Acoustic Control to practical engineering. A good actuator arrangement not only achieves a more effective control effect, but also reduces the required control energy, and a good sensor arrangement can help to collect more obvious and useful information. However, in some commonly used optimization programs, the influence of noise radiation is often ignored and only the controllability of structural vibration is concerned, which may cause the control force to control some modes with low noise radiation, but the modes that need to be controlled cannot be controlled. Therefore, this paper proposes a location optimization method of piezoelectric actuators and sensors in active noise control based on acoustic radiation, and formulates a new cost function, that is, the acoustic power is added as a weight function to the optimization criterion, so that the control energy can control these strong radiation modes as much as possible; at the same time, the Multi-Verse Optimizer algorithm is also improved, and through the optimization of the wormhole existence probability and travelling distance rate, the global search ability of the algorithm is improved to avoid the algorithm from entering the local in-depth development. In addition, the MVO algorithm suitable for continuous variables is discretized to adapt to the optimization problem in this paper.
Bibliography:SMS-113740.R1
ISSN:0964-1726
1361-665X
DOI:10.1088/1361-665X/ac8210