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扫频脉冲激励法在不同激光辐照参数下增强光声弹性波。

Sweep Pulse Excitation Method for Enhancing Photoacoustic Elastic Waves at Different Laser Irradiation Parameters.

机构信息

Faculty of Biology-Oriented Science and Technology, Kindai University, Wakayama 649-6493, Japan.

Department of Orthopedic Surgery, Keio University School of Medicine, Tokyo 160-8582, Japan.

出版信息

Sensors (Basel). 2022 Jul 3;22(13):5025. doi: 10.3390/s22135025.

DOI:10.3390/s22135025
PMID:35808520
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9269738/
Abstract

Laser remote sensing using a sweep pulse excitation method, in which a laser beam is irradiated at the same repetition frequency as the natural frequency, for enhancing photoacoustic elastic waves through resonance effect has been studied. The sweep pulse excitation method, which is based on the principle of detecting natural frequency fluctuations, such as hammering tests, can detect natural frequencies in the audible sound region with low average laser power and contribute to the convenience and low cost of an installation strength diagnosis of fastening bolts. In this study, we investigated the dynamics of the swept excitation method for optimization by evaluating the dependence of the laser irradiation conditions (pulse width, spot size, and average power) on different metal disc samples. We discovered that the magnitude of the photoacoustic elastic wave is proportional to the absorption of laser power, and the spatiotemporal dynamics can be explained through thermal diffusion phenomena. These findings contribute to the development of laser-sensing technology based on photoacoustic elastic waves.

摘要

采用扫频脉冲激励方法的激光遥感研究,其中激光束以与固有频率相同的重复频率照射,通过共振效应增强光声弹性波。扫频脉冲激励方法基于检测自然频率波动的原理,如敲击测试,可以用低平均激光功率检测可听声区域的固有频率,有助于安装强度诊断紧固螺栓的便利性和低成本。在这项研究中,我们通过评估激光照射条件(脉冲宽度、光斑大小和平均功率)对不同金属盘样品的依赖性,研究了扫频激励方法的动力学优化。我们发现光声弹性波的幅度与激光功率的吸收成正比,并且可以通过热扩散现象来解释其时空动力学。这些发现有助于基于光声弹性波的激光传感技术的发展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/59ba/9269738/2e9c7da0f26d/sensors-22-05025-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/59ba/9269738/211be569fbce/sensors-22-05025-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/59ba/9269738/ae99f8eb318d/sensors-22-05025-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/59ba/9269738/1e208a1e3d93/sensors-22-05025-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/59ba/9269738/2068eea85f6d/sensors-22-05025-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/59ba/9269738/402e4cb6f080/sensors-22-05025-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/59ba/9269738/3c2c8ef1df35/sensors-22-05025-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/59ba/9269738/2e9c7da0f26d/sensors-22-05025-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/59ba/9269738/211be569fbce/sensors-22-05025-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/59ba/9269738/0931ff754d3e/sensors-22-05025-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/59ba/9269738/ae99f8eb318d/sensors-22-05025-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/59ba/9269738/1e208a1e3d93/sensors-22-05025-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/59ba/9269738/2068eea85f6d/sensors-22-05025-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/59ba/9269738/402e4cb6f080/sensors-22-05025-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/59ba/9269738/3c2c8ef1df35/sensors-22-05025-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/59ba/9269738/2e9c7da0f26d/sensors-22-05025-g008.jpg

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Machine Learning-Based Diagnosis in Laser Resonance Frequency Analysis for Implant Stability of Orthopedic Pedicle Screws.基于机器学习的激光共振频率分析在骨科椎弓根螺钉植入稳定性诊断中的应用。
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Laser resonance frequency analysis of pedicle screw stability: A cadaveric model bone study.椎弓根螺钉稳定性的激光共振频率分析:尸体模型骨研究。
J Orthop Res. 2021 Nov;39(11):2474-2484. doi: 10.1002/jor.24983. Epub 2021 Jan 28.
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Laser Resonance Frequency Analysis: A Novel Measurement Approach to Evaluate Acetabular Cup Stability During Surgery.
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Sensors (Basel). 2019 Nov 8;19(22):4876. doi: 10.3390/s19224876.
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A study on the use of the Osstell apparatus to evaluate pedicle screw stability: An in-vitro study using micro-CT.一项使用 Osstell 仪器评估椎弓根螺钉稳定性的研究:使用微 CT 的体外研究。
PLoS One. 2018 Jun 28;13(6):e0199362. doi: 10.1371/journal.pone.0199362. eCollection 2018.
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