PIEZO-FIBER COMPOSITE SENSOR TAILORING USING GENETIC ALGO-RITHM

PIEZO-FIBER COMPOSITE SENSOR TAILORING USING GENETIC ALGO-RITHM

Almeida, A. S.; Medeiros, R.; Ribeiro, M. L.; Tita, V.; Marques, F.D.

Full Article:

The active aeroelastic control aims the reduction or elimination of harmful fluid-structure interaction effects. More recently, piezo-fiber composites, made from piezoelectric fibers embedded into composites, represent a major technological breakthrough for the manufacture of aerospace intelligent structures. The design and synthesis of intelligent sys-tems requires some effort to assess adequate sensor and actuator positioning and perfor-mance. Typically, sensors location or arrangements have been determined by using optimiza-tion approaches, in order to get the optimal performance in a particular system application. In the smart structures literature, it is usual to find investigations on PZT sensors arrange-ment optimization based on modal responses. Piezo-fiber composites may furnish appropriate framework to enhance sensor effective, in special when composite structures are considered. Moreover, each piezo-fiber composite sensor may be optimized, allowing adjustments of their internal laminate and PZT fibers, thereby reducing the number of required sensors and im-proving their integration to the primary structure. This paper presents an investigation on piezo-fiber composites optimization viewing their application as modal sensors or filtering. In this context, sensor tailoring is suggested by configuring the internal layers. The piezo-fiber composite sensor is assumed with internal layers and an extra embedded PZT fibers. Optimi-zation is performed to each layer direction by exploring a metrics on sensor response in mod-al coordinates for a range in the frequency domain. The finite element modeling is used to represent the dynamics of a uniform plate structure and the piezo-composite. The genetic al-gorithm is considered as optimization tool using modal parameters to achieve a cost function.

The active aeroelastic control aims the reduction or elimination of harmful fluid-structure interaction effects. More recently, piezo-fiber composites, made from piezoelectric fibers embedded into composites, represent a major technological breakthrough for the manufacture of aerospace intelligent structures. The design and synthesis of intelligent sys-tems requires some effort to assess adequate sensor and actuator positioning and perfor-mance. Typically, sensors location or arrangements have been determined by using optimiza-tion approaches, in order to get the optimal performance in a particular system application. In the smart structures literature, it is usual to find investigations on PZT sensors arrange-ment optimization based on modal responses. Piezo-fiber composites may furnish appropriate framework to enhance sensor effective, in special when composite structures are considered. Moreover, each piezo-fiber composite sensor may be optimized, allowing adjustments of their internal laminate and PZT fibers, thereby reducing the number of required sensors and im-proving their integration to the primary structure. This paper presents an investigation on piezo-fiber composites optimization viewing their application as modal sensors or filtering. In this context, sensor tailoring is suggested by configuring the internal layers. The piezo-fiber composite sensor is assumed with internal layers and an extra embedded PZT fibers. Optimi-zation is performed to each layer direction by exploring a metrics on sensor response in mod-al coordinates for a range in the frequency domain. The finite element modeling is used to represent the dynamics of a uniform plate structure and the piezo-composite. The genetic al-gorithm is considered as optimization tool using modal parameters to achieve a cost function.

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DOI: 10.5151/meceng-wccm2012-18527

Referências bibliográficas

• [1] ABREU, G. L. C. M. de; RIBEIRO, J. F.; STEFFEN, JR., V.. Finite element modeling of a plate with localized piezoelectric sensors and actuators. J. Braz. Soc. Mech. Sci. Andamp;Eng., Rio de Janeiro, v. 26, n. 2, June 2004 .
• [2] DIAMANTI, K.; SOUTIS, C. Structural health monitoring techniques for aircraft composite structures. Progress in Aerospace Sciences, v. 46, n. 8, p. 342-352, Nov 2010.
• [3] GOLDBERG, D. E. Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, 1989.
• [4] JIAN, K.; FRISWELL, M. I. Distributed modal sensors for rectangular plate structures. Journal of Intelligent Material Systems and Structures, v. 18, n. 9, p. 939-948, Sep 2007.
• [5] LAM, K.Y. et al. A finite-element model for piezoelectric composite laminates. Smart Materials Strucutres, Bristol, v.6, n.5, p583-591, oct 1997.
• [6] MATWEB, http://www.matweb.com
• [7] MEIROVITCH, L.; BARUH, H. CONTROL OF SELF-ADJOINT DISTRIBUTED-PARAMETER SYSTEMS. Journal of Guidance Control and Dynamics, v. 5, n. 1, p. 60-66, 1982.
• [8] PAGANI, C. C.; TRINDADE, M. A. Optimization of modal filters based on arrays of piezoelectric sensors. Smart Materials Andamp; Structures, v. 18, n. 9, p. 12, Sep 2009.
• [9] PIEZO SYSTEMS, INC., Manfacture''s catalog, http://www.piezo.com/catalog7C.pdf
• [10] PREUMONT, A. et al. Spatial filters in structural control. Journal of Sound and Vibration, v. 265, n. 1, p. 61-79, Jul 2003.
• [11] RAMESH, K; NARAYANAN, S. The Optimal Location of piezoelectric Actuators and Sensors for vibration control of plates. Smart Materials Strucutres, v.6, n.6 ,struct 16 2680, nov 2007.
• [12] SODANO, H. A.; PARK, G.; INMAN, D. J. Estimation of electric charge output for piezoelectric energy harvesting. Strain, v. 40, n. 2, p. 49-58, May 2004.

Como citar:

Almeida, A. S.; Medeiros, R.; Ribeiro, M. L.; Tita, V.; Marques, F.D.; "PIEZO-FIBER COMPOSITE SENSOR TAILORING USING GENETIC ALGO-RITHM", p-1722-1736. In: In Proceedings of the 10th World Congress on Computational Mechanics [= Blucher Mechanical Engineering Proceedings, v. 1, n. 1]. São Paulo: Blucher, 2014.
ISSN 23580828, DOI 10.5151/meceng-wccm2012-18527