Investigation of Dynamic Behavior of Smart Piezoelectric Actuators Using Artificial Neural Networks

Majlesi Journal of Electrical Engineering

مقاله 9، دوره 6، شماره 1، خرداد 2012   

نوع مقاله: Review Article

نویسندگان

Sepideh Ebrahimi^{* 1}؛ Somayyeh Shahbazi²؛ Yaser Shahbazi³؛ Ehsan Delavari³

¹Young Researchers Club, Aligodarz Branch, Islamic Azad University, Aligodarz, Iran

²Omid Nahavand Higher Education/Electronic Group, Nahavand, Iran

³Sahand University of Technology/ Civil Department, Tabriz, Iran

چکیده

The purpose of this study is to investigate microelectromechanical behavior of smart piezoelectric actuators using Artificial Neural Networks due to simple, multi harmonic and dynamic pulse excitations. Regarding to complexity and time-consuming analyses of vibration of smart structures, existing classical models are often insufficient. Nowadays, artificial intelligence tools are used for modeling such complex phenomena. The theoretical model is a three-layer piezoelectric composite beam that behaves as an axial actuating mechanism. This actuator consists of an elastic core sandwiched between two piezoelectric active outer layers. The piezoelectric layers are polarized transversely, i.e., the polarization vector is parallel to the applied electric field intensity vector. For initializing the electromechanical effect, an electric field is applied to the piezoelectric layers. The finite element modeling is constructed using ANSYS. Then, harmonic and dynamic vibration analyses are performed and the responses of smart beam are calculated. The required data used for artificial intelligence were collected from vibration analyses. Obtained results demonstrate that artificial neural network is in good agreement with observed values.

کلیدواژه‌ها

Young Researchers Club؛ en؛ Piezoelectric actuators؛ Islamic Azad University؛ Harmonic and Dynamic Vibration؛ Aligodarz branch؛ Artificial Neural Networks؛ Iran

مراجع

[1] Bailey T, Hubbard JE Jr.. “Distributed piezoelectric polymer active vibration control of a cantilever beam”. Journal of Guidance Control and Dynamics 1985;8:605–11.

[2] Lee CK, Moon FC. “Laminated piezopolymer plates for torsion and bending sensors and actuators”. Journal of Acoustics Society of America 1989;85:2432–9.

[3] Wang BT, Rogers CA. “Laminate plate theory for spatially distributed induced strain actuators”. Journal of Composite Materials 1991;25:433–52.

[4] Ha SK, Keilers C, Chang FK. “Finite element analysis of composite structures containing distributed piezoceramic sensors and actuators”. AIAA Journal 1992;30:772–80.

[5] Kim J, Varadan VV, Varadan VK, Bao XQ. “Finite element modelling of a smart cantilever plate and comparison with experiments”. Smart Materials and Structures 1996;5:165–70.

[6] Tzou HS, Tseng CI. “Distributed piezoelectric sensor/actuator design for dynamic measurement/control of distributed parameter system”. Journal of Sound and Vibration 1990;138:17–34.

[7] Robinson DH, Reddy JN. “Analysis of piezoelectrically actuated beams using a layer-wise displacement theory”. Computers and Structures 1991;41:265–79.

[8] Saravanos DA, Heyliger PR. “Coupled layer-wise analysis of composite beams with embedded piezoelectric sensors and actuators”. J Intell Mater Syst Struct 1995;6:350–63.

[9] Crawley EF, de Luis J. “Use of piezoelectric actuators as elements of intelligent structures”. AIAA Journal 1987;25:1373–85.

[10] Milsom RF, Reilly NHC, Redwood M. “Analysis of generation and detection of surface and bulk acoustic waves by interdigital transducer”. IEEE Trans Sonics and Ultra 1977;SU-24:147–66.

[11] Monkhouse RSC, Wilcox PW, Dalton RP, Cawley P. “The rapid monitoring of structures using interdigital Lamb wave transducers”. Smart Materials and Structures 2000;9:304–9.

[12] Morgan DP. History of SAW devices. IEEE International Frequency Control, 1998;439–60.

[13] Chandrashekhara K, Bhatia K. “Active buckling control of smart composite plates—finite-element analysis”. Smart Materials and Structure 1993;2:31–9.

[14] Roundy, S., Wright, P. K. and Rabaey, “A study of low level vibrations as a power source for wireless sensor nodes, ” Computer Communications, Vol. 26, pp. 1131- 1144, 2003.

[15] Sodano, H. A., Park, G., and Inman, D. J. “Estimation of electric charge output for piezoelectric energy harvesting,” Journal of Strain, Vol. 40, pp. 49-58, 2004.

[16] Roundy, S. et al. “Improving power output for vibration-based energy scavengers, ” IEEE Pervasive Comput. 4. pp. 28, 2005.

[17] Stephen, N. G. “On energy harvesting from ambient vibration, ” Journal of Sound and Vibration, 293, 409–25, 2006.

[18] Shenck, N. and Paradiso, “Energy scavenging with shoe-mounted piezoelectrics, ” IEEE Micro, Vol. 21, No. 3, 2001, pp. 30–42, 2001.

[19] ASCE Task Committee on Application of Artificial Neural Networks in Hydrology, Artificial neural networks in hydrology 1: Preliminary concepts. J. Hydrol. Eng. 5(2),115-123, 2000a.

[20] ASCE Task Committee on Application of Artificial Neural Networks in Hydrology, Artificial neural networks in hydrology. 2: Hydrologic applications. J. Hydrol. Eng., 5(2), 124-137, 2000b.