Paper
29 July 2004 Equivalent circuit models for interpreting impedance perturbation spectroscopy data
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Abstract
As in-situ structural integrity monitoring disciplines mature, there is a growing need to process sensor/actuator data efficiently in real time. Although smaller, faster embedded processors will contribute to this, it is also important to develop straightforward, robust methods to reduce the overall computational burden for practical applications of interest. This paper addresses the use of equivalent circuit modeling techniques for inferring structure attributes monitored using impedance perturbation spectroscopy. In pioneering work about ten years ago significant progress was associated with the development of simple impedance models derived from the piezoelectric equations. Using mathematical modeling tools currently available from research in ultrasonics and impedance spectroscopy is expected to provide additional synergistic benefits. For purposes of structural health monitoring the objective is to use impedance spectroscopy data to infer the physical condition of structures to which small piezoelectric actuators are bonded. Features of interest include stiffness changes, mass loading, and damping or mechanical losses. Equivalent circuit models are typically simple enough to facilitate the development of practical analytical models of the actuator-structure interaction. This type of parametric structure model allows raw impedance/admittance data to be interpreted optimally using standard multiple, nonlinear regression analysis. One potential long-term outcome is the possibility of cataloging measured viscoelastic properties of the mechanical subsystems of interest as simple lists of attributes and their statistical uncertainties, whose evolution can be followed in time. Equivalent circuit models are well suited for addressing calibration and self-consistency issues such as temperature corrections, Poisson mode coupling, and distributed relaxation processes.
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R. Lowell Smith "Equivalent circuit models for interpreting impedance perturbation spectroscopy data", Proc. SPIE 5391, Smart Structures and Materials 2004: Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems, (29 July 2004); https://doi.org/10.1117/12.539035
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KEYWORDS
Mathematical modeling

Circuit switching

Data modeling

Dielectric spectroscopy

Sensors

Structural health monitoring

Spectroscopy

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