Presentation + Paper
11 April 2017 Thermal stress characterization using the electro-mechanical impedance method
Xuan Zhu, Francesco Lanza di Scalea, Mahmood Fateh
Author Affiliations +
Abstract
This study examines the potential of the Electro-Mechanical Impedance (EMI) method to provide an estimation of the developed thermal stress in constrained bar-like structures. This non-invasive method features the easiness of implementation and interpretation, while it is notoriously known for being vulnerable to environmental variability. A comprehensive analytical model is proposed to relate the measured electric admittance signatures of the PZT element to temperature and uniaxial stress applied to the underlying structure. The model results compare favorably to the experimental ones, where the sensitivities of features extracted from the admittance signatures to the varying stress levels and temperatures are determined. Two temperature compensation frameworks are proposed to characterize the thermal stress states: (a) a regression model is established based on temperature-only tests, and the residuals from the thermal stress tests are then used to isolate the stress measurand; (b) the temperature-only tests are decomposed by Principle Components Analysis (PCA) and the feature vectors of the thermal stress tests are reconstructed after removal of the temperaturesensitive components. For both methods, the features were selected based on their performance in Receiver Operating Characteristic (ROC) curves. Experimental results on the Continuous Welded Rails (CWR) are shown to demonstrate the effectiveness of these temperature compensation methods.
Conference Presentation
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Xuan Zhu, Francesco Lanza di Scalea, and Mahmood Fateh "Thermal stress characterization using the electro-mechanical impedance method", Proc. SPIE 10164, Active and Passive Smart Structures and Integrated Systems 2017, 1016407 (11 April 2017); https://doi.org/10.1117/12.2258155
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KEYWORDS
Structural health monitoring

Capacitance

Dielectrics

Environmental sensing

Ceramics

Principal component analysis

Feature extraction

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