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Structural Health Monitoring
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Circuit Analysis of Impedance-based Health Monitoring of Beams Using Spectral Elements

Daniel M. Peairs

Center for Intelligent Material Systems and Structures, Virginia Polytechnic Institute and State University, 310 Durham Hall (Mailcode 0261), Blacksburg VA 24061-0261, USA; dpeairs{at}vt.edu

Daniel J. Inman

Center for Intelligent Material Systems and Structures, Virginia Polytechnic Institute and State University, 310 Durham Hall (Mailcode 0261), Blacksburg VA 24061-0261, USA

Gyuhae Park

Los Alamos National Laboratory, Engineering Sciences and Applications Division, Los Alamos, NM 87545, USA

A model is generally not needed for the basic damage identification problem when using the electromechanical impedance-based method of structural health monitoring (SHM). However, modeling becomes necessary when more information is needed for more complex functions of the SHM system, such as estimation of remaining life. In addition, suitable models would aid in more accurately identifying and locating damage and in designing the SHM system. Since impedance-based SHM relies on high frequency excitation of the structure using piezoelectric patches, finite element modeling may not be computationally efficient. In this study, the spectral element method (SEM) is used in combination with electric circuit analysis for impedance modeling. SEM more accurately models higher frequency vibrations than finite element methods since the mass is modeled exactly and it incorporates higher order models more easily. Simulations of sensor multiplexing, high frequency response, and the inclusion of damage are presented. Experimental verification is also included.

Key Words: impedance method • spectral element method • high frequency • health monitoring • self-sensing • piezoelectric

Structural Health Monitoring, Vol. 6, No. 1, 81-94 (2007)
DOI: 10.1177/1475921707072621


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Xianhua Liu and R. Paurobally
Robust Damage Metric in Terms of Magnitude and Phase for Impedance-based Structural Health Monitoring
Structural Health Monitoring, July 1, 2009; 8(4): 303 - 311.
[Abstract] [PDF]