Paper
29 July 2004 Frequency-response-based damage detection approach using a shunted piezoelectric transducer with variable inductance
Jiong Tang, Yu Ding
Author Affiliations +
Abstract
Since damage usually reduces stiffness, frequency responses of a structure can be used to detect damage where the variation/decrease in natural frequencies is used as indicator. Although frequency responses are easy to measure with a small number of sensors, they are global reflections of the system dynamic property and one single FRF oftentimes lacks the sensitivity for local damage detection. In addition, locating damage is difficult as it normally requires a large number of measured natural frequency shifts. In this paper we propose a new frequency response based approach by integrating piezoelectric transducer with variable inductance to the host mechanical structure. A piezoelectric shunt circuit could significantly change the system dynamic responses. While frequency responses can be easily measured for such system (for example, by applying voltage to the piezoelectric actuators), varying the inductance can lead to a family of frequency responses. By doing so, one can get much more complete “scanned” reflection of the possible damage within the mechanical structure. The family of frequency responses provides a much larger dataset for more accurate and reliable damage detection. In this paper, an inverse sensitivity based detection algorithm is formulated and the performance improvement due to the integration of variable inductive piezoelectric shunt is demonstrated.
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Jiong Tang and Yu Ding "Frequency-response-based damage detection approach using a shunted piezoelectric transducer with variable inductance", 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/10.1117/12.539562
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Cited by 1 scholarly publication.
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KEYWORDS
Damage detection

Inductance

Transducers

Actuators

Intelligence systems

Detection and tracking algorithms

Data modeling

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