Direct integration of SAW resonators on industrial metal for structural health monitoring applications

Author:

Mengue PORCID,Hage-Ali S,Zhgoon S,Paulmier Baptiste,Floer Cécile,Bartoli FlorianORCID,Elmazria O

Abstract

Abstract Surface acoustic wave (SAW) sensors are very promising for structural health monitoring (SHM) applications as they have the advantages of being robust, passive (batteryless), remotely interrogated (wireless) and can even be packageless. This paper describes ultralow-profile SAW resonators that can be directly fabricated and integrated on metallic parts in industrial facilities. They are based on piezoelectric thin films (ZnO) which are directly sputtered on polished industrial titanium (Ti) and stainless steel. With this approach, no sensor glue-bonding to the target is needed, and measurement errors related to this step are avoided. Demonstrator devices have been studied numerically and experimentally. The structural properties of the ZnO thin films were characterized through x-ray diffraction and atomic force microscopy. A preferred orientation (002) was achieved with a roughness of 50 nm on the top surface. Resonators were microfabricated and their functional parameters (i.e. resonance frequency, quality factor and electromechanical coupling) were extracted through impedance measurements and fitted with a Butterworth-van Dyke model. By increasing applied temperatures (up to 450 °C) and the strain (up to 1800 μϵ), a linear decrease of the resonance frequency has been shown. A temperature coefficient of frequency of −46.4 ppm °C−1 and a good strain sensitivity (1.49 ppmμϵ−1) were obtained, thus making the structure promising as a high temperature and strain sensing element in industrial SHM applications.

Funder

FEDER

FEDER-FSE & ICEEL

Agence Nationale de la Recherche

Publisher

IOP Publishing

Subject

Electrical and Electronic Engineering,Mechanics of Materials,Condensed Matter Physics,General Materials Science,Atomic and Molecular Physics, and Optics,Civil and Structural Engineering,Signal Processing

Reference27 articles.

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