aser Doppler vibrometry and wavefield analysis have recently shown great potential for nondestructive evaluation, structural health monitoring, and studying wave physics. However, there are limited studies on these approaches for viscoelastic soft materials, especially, very few studies on the laser Doppler vibrometer (LDV)-based acquisition of time–space wavefields of dispersive shear waves in viscoelastic materials and the analysis of these wavefields for characterizing shear wave dispersion and evaluating local viscoelastic property distributions. Therefore, this research focuses on developing a piezo stack-LDV system and shear wave time–space wavefield analysis methods for enabling the functions of characterizing the shear wave dispersion and the distributions of local viscoelastic material properties. Our system leverages a piezo stack to generate shear waves in viscoelastic materials and an LDV to acquire time–space wavefields. We introduced space-frequency-wavenumber analysis and least square regression-based dispersion comparison to analyze shear wave time–space wavefields and offer functions including extracting shear wave dispersion relations from wavefields and characterizing the spatial distributions of local wavenumbers and viscoelastic properties (e.g., shear elasticity and viscosity). Proof-of-concept experiments were performed using a synthetic gelatin phantom. The results show that our system can successfully generate shear waves and acquire time–space wavefields. They also prove that our wavefield analysis methods can reveal the shear wave dispersion relation and show the spatial distributions of local wavenumbers and viscoelastic properties. We expect this research to benefit engineering and biomedical research communities and inspire researchers interested in developing shear wave-based technologies for characterizing viscoelastic materials.
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Development of a Laser Vibrometer-Based Shear Wave Sensing System for Characterizing Mechanical Properties of Viscoelastic Materials
Abstract Characterizing the mechanical properties of viscoelastic materials is critical in biomedical applications such as detecting breast cancer, skin diseases, myocardial diseases, and hepatic fibrosis. Current methods lack the consideration of dispersion curves that depend on material properties and shear wave frequency. This paper presents a novel method that combines noncontact shear wave sensing and dispersion analysis to characterize the mechanical properties of viscoelastic materials. Our shear wave sensing system uses a piezoelectric stack (PZT stack) to generate shear waves and a laser Doppler vibrometer (LDV) integrated with a 3D robotic stage to acquire time-space wavefields. Next, an inverse method is employed for the wavefield analysis. This method leverages multi-dimensional Fourier transform and frequency-wavenumber dispersion curve regression. Through proof-of-concept experiments, our sensing system successfully generated shear waves and acquired its timespace wavefield in a customized viscoelastic phantom. After dispersion curve analysis, we successfully characterized two material properties (shear elasticity and shear viscosity) and measured shear wave velocities at different frequencies.
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- Award ID(s):
- 2243771
- PAR ID:
- 10519345
- Publisher / Repository:
- American Society of Mechanical Engineers
- Date Published:
- ISBN:
- 978-0-7918-8752-3
- Format(s):
- Medium: X
- Location:
- Austin, Texas, USA
- Sponsoring Org:
- National Science Foundation
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