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A data-driven temperature compensation approach for Structural Health Monitoring using Lamb waves

Article dans une revue avec comité de lecture
Author
FENDZI, Claude
COFFIGNAL, Gérard
ccMECHBAL, Nazih
86289 Laboratoire Procédés et Ingénierie en Mécanique et Matériaux [PIMM]
ccGUSKOV, Mikhail
ccRÉBILLAT, Marc

URI
http://hdl.handle.net/10985/11239
DOI
10.1177/1475921716650997
Date
2016
Journal
Structural Health Monitoring

Abstract

This paper presents a temperature compensation method for Lamb wave structural health monitoring. The proposed approach considers a representation of the piezo-sensor signal through its Hilbert transform that allows one to extract the amplitude factor and the phase shift in signals caused by temperature changes. An ordinary least square (OLS) algorithm is used to estimate these unknown parameters. After estimating these parameters at each temperature in the operating range, linear functional relationships between the temperature and the estimated parameters are derived using the least squares method. A temperature compensation model is developed based on this linear relationship that allows one to reconstruct sensor signals at any arbitrary temperature. The proposed approach is validated numerically and experimentally for an anisotropic composite plate at different temperatures ranging from Formula to Formula . A close match is found between the measured signals and the reconstructed ones. This approach is interesting as it needs only a limited set of piezo-sensor signals at different temperatures for model training and temperature compensation at any arbitrary temperature. Damage localization results after temperature compensation demonstrate its robustness and effectiveness.

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