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High Frequency Acoustic Sensor Dedicated to the High Resolution Measurement of Mechanical Properties
Pierre-Antoine Meignen, Emmanuel Le Clezio, Gilles Despaux
To cite this version:
Pierre-Antoine Meignen, Emmanuel Le Clezio, Gilles Despaux. High Frequency Acoustic Sensor Ded- icated to the High Resolution Measurement of Mechanical Properties. Physics Procedia, Elsevier, 2015, 70, pp.424 - 427. �10.1016/j.phpro.2015.08.134�. �hal-01627848�
Physics Procedia 70 ( 2015 ) 424 – 427
1875-3892 © 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Peer-review under responsibility of the Scientific Committee of ICU 2015 doi: 10.1016/j.phpro.2015.08.134
ScienceDirect
2015 International Congress on Ultrasonics, 2015 ICU Metz
High frequency acoustic sensor dedicated to the high resolution measurement of mechanical properties
Pierre-Antoine Meignena,b, Emmanuel Le Clézioa,b, Gilles Despauxa,b*
a University of Montpellier, IES UMR 5214, F-34000 Montpellier, France
b CNRS, IES UMR 5214, F-34000 Montpellier, France
Abstract
Through acoustic signature, scanning acoustic microscopy can be used to quantify local mechanical properties of a medium thanks to the generation of surface waves, mostly Rayleigh waves. Despite being quite effective, this method requires to evaluate the mechanical properties of a single point the acquisition of many ultrasonic signals. This process is then time-consuming and is hardly adaptable to quantitative imaging. The solution considered in this paper to speed-up the method is to design a multi- element sensor allowing the extraction of information on Rayleigh waves with a reduced number of acquisitions. The work is conducted along two axes. As a first step, a model allowing the simulation of the acoustic wave behavior at a fluid/solid interface is developed. This model leads to a better understanding of the characterization of the mechanical properties and to the definition of an adapted sensor’s design. As a second step, an experimental method for acoustic field reconstruction is used to characterize the multi-elements sensor and measurements of mechanical properties were done.
© 2015 The Authors. Published by Elsevier B.V.
Peer-review under responsibility of the Scientific Committee of 2015 ICU Metz.
Keywords: Mechanical properties; High frenquency; Sensor;
1. Introduction
The mechanical characterization of a material is possible using acoustic waves. It has the advantage of being non- destructive compared to other well-known methods such as the three points bending or the indentation methods which induce a deformation of the material. The acoustical methods are based on the measurement of the
* Corresponding author: Gilles Despaux Tel.: +0-033-467-144-282; fax: +0-033-467-149-252.
E-mail address: [email protected]
© 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Peer-review under responsibility of the Scientific Committee of ICU 2015
Pierre-Antoine Meignen et al. / Physics Procedia 70 ( 2015 ) 424 – 427 425
propagation velocities of a material that are the longitudinal wave, the transverse wave or the Rayleigh wave velocities. These three parameters are linked through Viktorov’s formula [Dieulesaint 1974]:
VR=VT
0.718− VT
VL
§
©¨ ·
¹¸
2
0.75− VT VL
§
©¨ ·
¹¸
2 . (1)
The longitudinal and transverse velocities can be measured thanks to the ultrasonic pulse-echo technique yielding the identification of the mechanical properties along proper directions [Weglewski 2013]. The main drawback of this method is its non-applicability to objects with irregular geometry or small dimensions.
On the other hand, the Scanning Acoustic Microscopy (SAM) allows the simultaneous measure of both longitudinal and Rayleigh wave velocities. In addition to its non-destructiveness, the main advantage of this method is that the mechanical properties can be evaluated point by point with a resolution depending on the frequency – the higher the frequency, the higher the resolution. This method relies on the measurement of the acoustical signature of a material (the V(z) curve) which is done by acquiring signals at multiple defocusing point. A one-point evaluation being currently seconds long, this multiplicity makes prohibitive the obtainment of a map of the mechanical properties.
This paper describes a high frequency multi-element transducer that should allow hastening the measurement of the mechanical properties by reducing the number of needed SAM acquisitions. This sensor would permit the simultaneous mapping of both the mechanical properties and the topography of a material. Firstly, a quick introduction to the SAM mechanical properties’ evaluation will be done. Then the multi-element specificities will be described before presenting the modelling of its acoustic behavior.
2. Mechanical characterization with acoustic microscopy
A SAM device includes a sensor with a spherical lens allowing the focusing of the acoustic energy on a spot whose dimensions are dependent on the wavelength. The higher the resolution is wanted the higher the frequency of the transducer is required. The focused sensor can be used to measure the mechanical properties of a sample by generating Rayleigh waves. They are surface acoustic waves that travel with a velocity VR that can be directly related to the longitudinal velocity VL and the transverse velocity VT thanks to Viktorov’s formula (Eq.1). The identification of VR allows overcoming the necessity of measuring the transverse velocity.
The Rayleigh wave can be generated inside the material by fixing the incidence of an acoustic external plane wave to a specific angle, the Rayleigh angle șR. For V(z) applications, this latter is included inside the focused beam of the SAM device emitting in water to the surface of the tested sample (Fig. 1(a)) [Attal 1998]. During its propagation along the surface of the material, the Rayleigh wave reemits, at the same angle, energy into the coupling medium. The ray theory indicates that two main paths are available for the acoustical waves to be reflected to the sensor while the other paths will be deflected. These two waves, the specular wave (I) and the Rayleigh wave (II) will then recombine on the transducer surface, their relative phase depending on the distance of the sensor from the material. Changing the sensor’s z-position leads to the presence of maxima and minima in the amplitude of the output signal. This is the V(z) curve (Fig. 1(b)) allowing the extraction of the Rayleigh wave velocity and therefore the mechanical properties of the tested material [Attal 1992].
As this method needs for a one-point characterization multiple acquisitions along the Z-axis, vertical displacement of the sensor is usually ensured by motorized linear stages. As a consequence, a 2D mapping of a material in the XY plane would be as time consuming as a 3D imaging of the material yielding unfeasible industrial application. To circumvent this constraint, the solution considered here is to de-correlate the specular and Rayleigh wave acquisitions thanks to a multi-element sensor.
3. Multi-element sensor
A multi-element sensor was designed to separate the emission and the reception of the specular waves and the Rayleigh wave. The objective of this sensor is to measure the time of flight of both waves without interferences that
occur when using a classic mono-element sensor. The sensor active part is separated into two piezoelectric elements:
a central part, respectively a ring, that will generate and receive the specular wave, respectively the Rayleigh waves.
The sensor elements have to be sized accordingly with a ring inner and outer diameters that must include the diameter of the microscope focusing lens corresponding to the angle șR. On a side note, it is also possible to split the ring into two lateral elements as seen on Fig. 1(c) in order to allow the analysis of anisotropic materials.
Figure 1: a) Rayleigh wave generation and interferences with specular waves, b) Acoustic signature, c) Electrodes pattern.
4. Rayleigh integral modelling
To anticipate the behaviour of the sensor and to perform a first verification on its relevance for mechanical properties’ measurement, a modelling of the sensor’s acoustical field was performed. This modelling was done by solving the Rayleigh integral while considering a set of individual sources spread amongst a rigid surface (the radiating structure). It yields the resulting pressure expression of Eq. (2):
0 ( )
( , ) 2
jkR
j t n s
S
j v r e
p r t e dS
R ωρ ω
π
= ³ − (2)
with Ȧ the ultrasonic pulsation, ȡ0 the density of the medium, S the rigid surface, dS a surface element, vn the normal speed at the surface, rs the position of the individual source, r the position where is calculated the pressure p and R the distance between these two positions.
As seen in Fig. 1(a), the sensor presents a delay line and a lens. The integral must then be solved twice to calculate the pressure field after the lens in the coupling medium (usually water). To do so, both the piezoelectric elements and the lens are discretized into individual sources. The integral is first solved on the lens surface to get the pressure radiated from the piezoelectric elements. Then, a second integral is calculated after the lens by weighting each source of the lens by the pressure previously coming from the piezoelectric elements.
5. Modelling results
Fig. 2 presents the normalized acoustical fields (calculated with the model) of the central and the two lateral electrodes, computed in a plan XZ after the lens. They should be compared to the acoustical field of a classic sensor with a unique electrode but as it is qualitatively similar to the field of the central electrode, this latter won’t be presented here. Yet these results prove the appearance of lateral lobes in the field coming from the ring electrodes.
They do not exist in the central electrode field.
The Fig. 3 presents the mesh plot of the normalized acoustical fields of the central and the two lateral electrodes in the lens focal plan. Both fields are normalized by the maximum power of the central electrode field to allow direct comparison. This figure clearly shows two different pressure repartition profiles, the central electrode generating a central peak of power corresponding to the specular wave while the lateral electrodes primarily generate lateral lobes. Keeping in mind the focusing process induced by the lens, these lateral lobes are mainly due to acoustical waves propagating towards the material within a small range of incidence angles. Therefore, by well- designing the sensor, it should possible to use these lateral lobes to control the generation of Rayleigh waves.
Pierre-Antoine Meignen et al. / Physics Procedia 70 ( 2015 ) 424 – 427 427
Figure 2: Acoustical field pressure due to the central electrode (a) and acoustical field pressure due to the lateral electrodes (b) at 20MHz, in water (speed of sound 1500m.s-1) after a lens (diameter 6mm, depth 1.35mm and aperture 34°) engraved in a 40mm long silica delay line (speed
of sound 5850m.s-1).
Figure 3: Acoustical field pressure due to the central electrode (a) and acoustical field pressure due to the lateral electrodes (b) at the focal plan.
6. Conclusion
A modelling of the acoustical field pressure was presented. It was applied to a multi-element piezoelectric sensor with a central electrode and a ring electrode separated into two parts. It showed the relevance of such a pattern to separate the specular and the surface waves generated by a focused acoustic sensor. This yields a lot of advantages in the development of mechanical properties’ measurement tools and may lead to the imagery of such properties that is currently too time-consuming be done routinely in the industrial domain.
7. References
E. Dieulesaint, D. Royer, 1974, Ondes Elastiques dans les solides, Volume 1, Propagation libre et guidée.
W. Weglewski, K. Bochenek, M. Basista, Th. Schubert, U. Jehring, J. Litniewki, S. Mackiewicz, Comparative assessment of Young’s modulus measurements of metal-ceramic composites using mechanical and non-destructive tests and micro-CT based computational modeling, 2013, Computational Materials Science 77, 19-30.
J. Attal, L. Robert, G. Despaux, R. Caplain,, J.M. Saurel, 1992, New developments in scanning acoustic microscopy, Acoustical Imaging, Volume 19.
J. Attal, 1998, Microscopie acoustique.
