Noninvasive low-cycle fatigue characterization at high depth with photoacoustic eigen-spectrum analysis

Xiaoxiang Gao,Rong Zhu,Chao Tao,Xiaojun Liu

doi:10.1038/s41598-018-26140-x

Abstract

In this work, photoacoustic eigen-spectrum analysis was proposed for noninvasively characterizing the mechanical properties of materials. We theoretically predicted the relationship between the photoacoustic eigen-spectra of cylindrical optical absorbers and their mechanical properties. Experimental measurements of eigen-spectra extracted from photoacoustic coda waves agreed well with the theoretical predictions. We then applied the photoacoustic eigen-spectrum analysis for contactless monitoring of low-cycle fatigue damage. Experiments showed that the photoacoustic eigen-spectra were closely related to the degree of low-cycle fatigue. This study might enhance the contrast of photoacoustic imaging ford mechanical characterization.

Highlights

We studied the photoacoustic eigen-spectra of cylindrical optical absorbers and characterized the fatigue of materials by using photoacoustic eigen-spectrum analysis
We theoretically predicted the eigen-frequencies of cylindrical optical absorbers
Photoacoustic eigen-spectra extracted from experimental photoacoustic waves confirm the theoretical predictions

Summary

Introduction

Photoacoustic imaging (PAI), based on the photoacoustic effect, is a hybrid technique that combines the advantages of high ultrasonic resolution in deep tissues and strong optical contrast[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24]. All optical resonant ultrasound spectroscopy (RUS)[35,36,37] and laser ultrasonic methods[38,39,40,41] provide contactless techniques for the measurement of mechanical properties. These methods require direct detection of the surface vibration of samples via optical methods. It has been demonstrated that the eigen-vibration information and mechanical properties of a spherical object are imprinted in the generated photoacoustic coda waves These previous studies have demonstrated the proficiency of photoacoustic methods in mechanical characterization. We applied photoacoustic eigen-spectrum analysis to monitor the low-cycle fatigue of wires

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