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基于超声导波的结构健康监测与健康程度指数

Structural Health Monitoring Using Ultrasonic Guided-Waves and the Degree of Health Index.

机构信息

Department of Mechanical Engineering, University of Bristol, Bristol BS8 1TR, UK.

Electronic Design Group, University of the Basque Country (UPV/EHU), 48013 Bilbao, Spain.

出版信息

Sensors (Basel). 2021 Feb 2;21(3):993. doi: 10.3390/s21030993.

DOI:10.3390/s21030993
PMID:33540636
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7867255/
Abstract

This paper proposes a new damage index named (DoH) to efficiently tackle structural damage monitoring in real-time. As a key contribution, the proposed index relies on a pattern matching methodology that measures the time-of-flight mismatch of sequential ultrasonic guided-wave measurements using fuzzy logic fundamentals. The ultrasonic signals are generated using the transmission beamforming technique with a phased-array of piezoelectric transducers. The acquisition is carried out by two phased-arrays to compare the influence of pulse-echo and pitch-catch modes in the damage assessment. The proposed monitoring approach is illustrated in a fatigue test of an aluminum sheet with an initial notch. As an additional novelty, the proposed pattern matching methodology uses the data stemming from the transmission beamforming technique for structural health monitoring. The results demonstrate the efficiency and robustness of the proposed framework in providing a qualitative and quantitative assessment for fatigue crack damage.

摘要

本文提出了一种新的损伤指标(DoH),旨在有效地实时解决结构损伤监测问题。作为主要贡献,所提出的指标依赖于一种模式匹配方法,该方法使用模糊逻辑基础来测量顺序超声导波测量的飞行时间失配。超声信号是使用相控阵压电换能器的发射波束形成技术产生的。采集是通过两个相控阵来进行的,以比较在损伤评估中脉冲回波和对中模式的影响。所提出的监测方法在具有初始缺口的铝板的疲劳试验中得到了说明。作为另一个新颖之处,所提出的模式匹配方法使用来自发射波束形成技术的数据进行结构健康监测。结果表明,所提出的框架在提供疲劳裂纹损伤的定性和定量评估方面具有高效性和鲁棒性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f369/7867255/dbd08a800c9e/sensors-21-00993-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f369/7867255/9e11f816d4c0/sensors-21-00993-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f369/7867255/668945d8f55a/sensors-21-00993-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f369/7867255/0080386e7d8a/sensors-21-00993-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f369/7867255/711f06ca7322/sensors-21-00993-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f369/7867255/20cff3710b58/sensors-21-00993-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f369/7867255/3050ae63ce9e/sensors-21-00993-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f369/7867255/ab161d1cddc7/sensors-21-00993-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f369/7867255/f3cb86680f68/sensors-21-00993-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f369/7867255/76641db94c65/sensors-21-00993-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f369/7867255/dbd08a800c9e/sensors-21-00993-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f369/7867255/9e11f816d4c0/sensors-21-00993-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f369/7867255/668945d8f55a/sensors-21-00993-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f369/7867255/0080386e7d8a/sensors-21-00993-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f369/7867255/711f06ca7322/sensors-21-00993-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f369/7867255/20cff3710b58/sensors-21-00993-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f369/7867255/3050ae63ce9e/sensors-21-00993-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f369/7867255/ab161d1cddc7/sensors-21-00993-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f369/7867255/f3cb86680f68/sensors-21-00993-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f369/7867255/76641db94c65/sensors-21-00993-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f369/7867255/dbd08a800c9e/sensors-21-00993-g010.jpg

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